ADSC-derived exosomes provide neuroprotection in sepsis-associated encephalopathy by regulating hippocampal pyroptosis.

AIMS: Adipose-derived stem cell (ADSC)-derived exosomes have been recognized for their neuroprotective effects in various neurological diseases. This study investigates the potential neuroprotective effects of ADSC-derived exosomes in sepsis-associated encephalopathy (SAE). METHODS: Behavioral cognitive functions were evaluated using the open field test, Y-maze test, and novel object recognition test. Brain activity was assessed through functional magnetic resonance imaging (fMRI). Pyroptosis was measured using immunofluorescence staining and western blotting. RESULTS: Our findings indicate that ADSC-derived exosomes mitigate cognitive impairment, improve survival rates, and prevent weight loss in SAE mice. Additionally, exosomes protect hippocampal function in SAE mice, as demonstrated by fMRI evaluations. Furthermore, SAE mice exhibit neuronal damage and infiltration of inflammatory cells in the hippocampus, conditions which are reversed by exosome treatment. Moreover, our study highlights the downstream regulatory role of the NLRP3/caspase-1/GSDMD signaling pathway as a crucial mechanism in alleviating hippocampal inflammation. CONCLUSION: ADSC-derived exosomes confer neuroprotection in SAE models by mediating the NLRP3/caspase-1/GSDMD pathway, thereby ameliorating cognitive impairment.

Association between the functional connectivity of ventral tegmental area-prefrontal network and pure apathy in Parkinson's disease: a cross-sectional study.

Background: Apathy, characterized by diminished goal-directed behaviors, frequently occurs in patients with Parkinson's disease (PD). The dopamine-releasing neurons of the ventral tegmental area (VTA) have been closely related to this behavioral disruption and project widely to the corticolimbic areas, yet their functional and structural connectivity in regard to other brain regions remain unknown in patients with PD and pure apathy (PD-PA). This study thus aimed to characterize the alterations of functional connectivity (FC) of the VTA and white matter structural connectivity in PD-PA. Methods: In this study, 29 patients with PD-PA, 37 with PD but not pure apathy (PD-NPA), and 28 matched healthy controls (HCs) underwent T1-weighted, resting state functional magnetic resonance imaging, and diffusion tensor imaging scans. Patients of this cross-sectional retrospective study were consecutively recruited from The First Affiliated Hospital of Nanjing Medical University between April 2017 and October 2021. Meanwhile, HCs were consecutively recruited from the local community and the Health Examination Center of our hospital. An analysis of covariance and a general linear model were respectively conducted to investigate the functional and structural connectivity among three groups. The tract-based spatial statistics (TBSS) approach was used to investigate the white matter structural connectivity. Results: Patients with PD-PA showed reduced FC of the VTA with the left medial superior frontal gyrus (SFGmed) when compared to the patients with PD-NPA [t=-3.67; voxel-level P<0.001; cluster-level family-wise error-corrected P (PFWE)<0.05]. Relative to the HCs, patients with PD-PA demonstrated reduced FC of the VTA with the left SFGmed (t=-4.98; voxel-level P<0.001; cluster-level PFWE<0.05), right orbital superior frontal gyrus (SFGorb) (t=-5.08; voxel-level P<0.001; cluster-level PFWE<0.05), and right middle frontal gyrus (MFG) (t=-5.08; voxel-level P<0.001; cluster-level PFWE<0.05). Moreover, the reductions in VTA FC with the left SFGmed were associated with severe apathy symptoms in patients with PD-PA (r=-0.600; P=0.003). However, a TBSS approach did not reveal any significant differences in fiber tracts between the three groups. Conclusions: This study identified reduced FC within the mesocortical network (VTA-SFGmed) of patients with PD-PA. These findings may provide valuable information for administering neuromodulation therapies in the alleviation of apathy symptoms in those with PD.

Neural mechanisms underlying improved new-word learning with high-density transcranial direct current stimulation.

Neurobehavioral studies have provided evidence for the effectiveness of anodal tDCS on language production, by stimulation of the left Inferior Frontal Gyrus (IFG) or of left Temporo-Parietal Junction (TPJ). However, tDCS is currently not used in clinical practice outside of trials, because behavioral effects have been inconsistent and underlying neural effects unclear. Here, we propose to elucidate the neural correlates of verb and noun learning and to determine if they can be modulated with anodal high-definition (HD) tDCS stimulation. Thirty-six neurotypical participants were randomly allocated to anodal HD-tDCS over either the left IFG, the left TPJ, or sham stimulation. On day one, participants performed a naming task (pre-test). On day two, participants underwent a new-word learning task with rare nouns and verbs concurrently to HD-tDCS for 20 min. The third day consisted of a post-test of naming performance. EEG was recorded at rest and during naming on each day. Verb learning was significantly facilitated by left IFG stimulation. HD-tDCS over the left IFG enhanced functional connectivity between the left IFG and TPJ and this correlated with improved learning. HD-tDCS over the left TPJ enabled stronger local activation of the stimulated area (as indexed by greater alpha and beta-band power decrease) during naming, but this did not translate into better learning. Thus, tDCS can induce local activation or modulation of network interactions. Only the enhancement of network interactions, but not the increase in local activation, leads to robust improvement of word learning. This emphasizes the need to develop new neuromodulation methods influencing network interactions. Our study suggests that this may be achieved through behavioral activation of one area and concomitant activation of another area with HD-tDCS.

Exome functional risk score and brain connectivity can predict social adaptability outcome of children with autism spectrum disorder in 4 years' follow up.

Introduction: Autism Spectrum Disorder (ASD) is a common neurodevelopmental disorder emerging in early childhood, with heterogeneous clinical outcomes across individuals. This study aims to recognize neuroimaging genetic factors associated with outcomes of ASD after a 4-year follow-up. Methods: A total of 104 ASD children were included in this study; they underwent clinical assessments, MRI data acquisition, and the whole exome sequencing (WES). Exome functional risk score (EFRS) was calculated based on WES; and two modalities of brain connectivity were constructed based on MRI data, that is functional connectivity (FC) for functional MRI (fMRI), and individual differential structural covariance network (IDSCN) for structural MRI (sMRI), to explore the neuroimaging genetic biomarker of outcomes of ASD children. Results: Regression analysis found EFRS predicts social adaptability at the 4-year follow-up (Y = -0.013X + 9.29, p = 0.003). We identified 19 pairs of FC associated with autism symptoms severity at follow-up, 10 pairs of FC and 4 pairs of IDSCN associated with social adaptability at follow-up, and 10 pairs of FC associated with ASD EFRS by support vector regression (SVR). Related brain regions with prognostic predictive effects are mainly distributed in superior frontal gyrus, occipital cortex, temporal cortex, parietal cortex, paracentral lobule, pallidum, and amygdala for FC, and temporal cortex, thalamus, and hippocampus for IDSCN. Mediation model showed that ASD EFRS affects the social communication of ASD children through the mediation of FC between left middle occipital gyrus and left pallidum (RMSEA=0.126, CMIN=80.66, DF=42, p< 0.001, CFI=0.867, AIC=152). Discussion: Our findings underscore that both EFRS and brain connectivity can predict social adaptability, and that brain connectivity serving as mediator in the relationship of EFRS and behaviors of ASD, suggesting the intervention targets in the future clinical application.

Multimodal transformer graph convolution attention isomorphism network (MTCGAIN): a novel deep network for detection of insomnia disorder.

Background: In clinic, the subjectivity of diagnosing insomnia disorder (ID) often leads to misdiagnosis or missed diagnosis, as ID may have the same symptoms as those of other health problems. Methods: A novel deep network, the multimodal transformer graph convolution attention isomorphism network (MTGCAIN) is proposed in this study. In this network, graph convolution attention (GCA) is first employed to extract the graph features of brain connectivity and achieve good spatial interpretability. Second, the MTGCAIN comprehensively utilizes multiple brain network atlases and a multimodal transformer (MT) to facilitate coded information exchange between the atlases. In this way, MTGCAIN can be used to more effectively identify biomarkers and arrive at accurate diagnoses. Results: The experimental results demonstrated that more accurate and objective diagnosis of ID can be achieved using the MTGCAIN. According to fivefold cross-validation, the accuracy reached 81.29% and the area under the receiver operating characteristic curve (AUC) reached 0.8760. A total of nine brain regions were detected as abnormal, namely right supplementary motor area (SMA.R), right temporal pole: superior temporal gyrus (TPOsup.R), left temporal pole: superior temporal gyrus (TPOsup.L), right superior frontal gyrus, dorsolateral (SFGdor.R), right middle temporal gyrus (MTG.R), left middle temporal gyrus (MTG.L), right inferior temporal gyrus (ITG.R), right median cingulate and paracingulate gyri (DCG.R), left median cingulate and paracingulate gyri (DCG.L). Conclusions: The brain regions in the default mode network (DMN) of patients with ID show significant impairment (occupies four-ninths). In addition, the functional connectivity (FC) between the right middle occipital gyrus and inferior temporal gyrus (ITG) has an obvious correlation with comorbid anxiety (P=0.008) and depression (P=0.005) among patients with ID.

Revealing the mechanism of central pain hypersensitivity in primary dysmenorrhea: evidence from neuroimaging.

Background: Primary dysmenorrhea (PDM) is the most common problem in menstruating women. A number of functional magnetic resonance imaging (fMRI) study have revealed that the brain plays a crucial role in the pathophysiology of PDM. However, these results have been inconsistent, and there is a lack of a comprehensive fMRI study to clarify the onset and long-term effects of PDM. The aim of this study was thus to investigate the onset and long-term effects of PDM in a cohort of patients with PDM. Methods: This study employed a cross-sectional design with prospective data collection, in which 25 patients with PDM and 20 healthy controls (HCs) were recruited. The patients with PDM underwent fMRI scans both during the PDM during the pain phase (PDM-P) and nonpain phase (PDM-NP). The long-term effects of PDM on the brain was assessed by comparing PDM-NP findings with those of HCs, and the central mechanism of PDM was assessed by comparing the PDM-P findings with those of PDM-NP. To identify changes in brain function, the amplitude of low-frequency fluctuations and the regional homogeneity (ReHo) were measured. To assess changes in brain structure, voxel-based morphometry (VBM) was applied. The periaqueductal gray (PAG) was set as a region of for conducting seed-based whole-brain functional connectivity (FC) analysis. Subsequently, Pearson correlation analyses were employed to evaluate the associations between the abnormal brain region and the clinical information of the patients. Results: There were neither functional nor structural differences between patients in the PDM-NP and HCs. Compared with those in PDM-NP, those in PDM-P showed increased ReHo in the left dorsolateral prefrontal cortex (DLPFC) but decreased FC between PAG and right superior parietal gyrus, bilateral inferior parietal gyrus, right calcarine gyrus, left superior occipital gyrus, left precentral gyrus, right DLPFC, and left crus I of the cerebellar hemisphere. Conclusions: The results from this study suggest that the mechanism of central pain hypersensitivity of PDM may be related to the disorder of the FC between the PAG and descending pain modulation system, default mode network (DMN), and occipital lobe. These findings could help us better understand the pathophysiology of PDM from a neuroimaging perspective.

The role of stimulant washout status in functional connectivity of default mode and fronto-parietal networks in children with neurodevelopmental conditions.

BACKGROUND: Stimulant medication is the primary pharmacological treatment for attention dysregulation and is commonly prescribed for children with Attention-Deficit/Hyperactivity Disorder (ADHD) and Autism. Neuroimaging studies of these groups commonly use a 24-48-hour washout period to mediate the effects of stimulant medication on functional connectivity (FC) metrics. However, the impact of washout on functional connectivity has received limited study. METHODS: We used fMRI data from participants with diagnosis of Autism and ADHD (and an off stimulant control) from the Adolescent Brain and Cognitive Development (ABCD) and Autism Brain Imaging Data Exchange (ABIDE) databases to explore the effect of simulant washout on FC. Connectivity within and between the default mode (DMN) and fronto-parietal networks (FPN) was examined, as these networks have previously been implicated in attention dysregulation and associated with stimulant medication usage. For each diagnostic group, we assessed effects in interconnectivity between DMN and FPN, intraconnectivity within DMN, and intraconnectivity within FPN. RESULTS: We found no significant effect of medication status in intra- and inter-connectivity of the DMN and the FPN in either diagnostic group. IMPLICATIONS: Our findings suggest that more information is needed about the effect of stimulant medication, and washout, on the FC of attention networks in clinical populations.

Tumor characteristics, brain functional activity, and connectivity of tinnitus in patients with vestibular schwannoma: a pilot study.

Background: The mechanism underlying tinnitus remains unclear, and when it coexists with vestibular schwannoma (VS), it can significantly diminish the quality of life for affected patients. This study aimed to determine the correlation between preoperative clinical characteristics of VS, postoperative changes in brain function, and tinnitus in patients with VS through a cohort study. Methods: We collected data from 80 patients with VS preoperatively and 28 patients with VS preoperatively and postoperatively, and recruited 28 healthy controls. We used Chi-squared tests and unpaired t-tests to identify clinical characteristics with a significant preoperative effect. We used paired t-tests to identify brain regions where patients demonstrated significant changes in amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) postoperatively. Tinnitus severity was evaluated using the Tinnitus Handicap Inventory (THI) and Visual Analogue Scale (VAS). Pearson correlation coefficients were applied to assess the relationship between the changes in ALFF and ReHo and the changes in THI and VAS scores postoperatively. We also conducted seed- and region of interest (ROI)-based functional connectivity (FC) analyses. Results: Before surgery, patients with VS with tinnitus (n=49) had smaller tumors (t=3.293; P<0.001), more solid tumor (χ2=4.559; P=0.033), and less extrusion into the cerebellum brain stem (χ2=10.345; P=0.001) than those without tinnitus (n=31). After surgery, the 28 patients with VS showed a significant reduction in ALFF in the left Cerebellum_Crus2 (a lobule in the cerebellum anatomy) (ROI 1) and a significant reduction in ReHo in the left Cerebellum_Crus1 (a lobule in the cerebellum anatomy) (ROI 2) and the right precuneus (ROI 3). Conversely, ReHo was significantly increased in the right precentral gyrus (ROI 4) [cluster-level P value family-wise error (PFWE) <0.05]. The changes in ALFF values were negatively correlated with changes in the VAS score (r=-0.32; P<0.05). The FC strengths of patients between ROI 2 and the left and right posterior cingulate gyrus were significantly decreased postoperatively [false discovery rate (FDR) correction; P<0.05]. Conclusions: Preoperative tinnitus in patients with VS may be influenced by tumor characteristics. The functional activities of brain regions are possibly altered postoperatively, which may be involved in the maintenance of postoperative tinnitus. Notably, the changes in ALFF are correlated with tinnitus.

Brain connectome-based imaging markers for identifiable signature of migraine with and without aura.

Background: Cortical spreading depression (CSD) has been considered the prominent theory for migraine with aura (MwA). However, it is also argued that CSD can exist in patients in a silent state, and not manifest as aura. Thus, the MwA classification based on aura may be questionable. This study aimed to capture whole-brain connectome-based imaging markers with identifiable signatures for MwA and migraine without aura (MwoA). Methods: A total of 88 migraine patients (32 MwA) and 49 healthy controls (HC) underwent a diffusion tensor imaging and resting-state functional magnetic resonance imaging scan. The whole-brain structural connectivity (SC) and functional connectivity (FC) analysis was employed to extract imaging features. The extracted features were subjected to an all-relevant feature selection process within cross-validation loops to pinpoint attributes demonstrating substantial efficacy for patient categorization. Based on the identified features, the predictive ability of the random forest classifiers constructed with the 88 migraine patients' sample was tested using an independent sample of 32 migraine patients (eight MwA). Results: Compared to MwoA and HC, MwA showed two reduced SC and six FC (five increased and one reduced) features [all P<0.01, after false discovery rate (FDR) correction], involving frontal areas, temporal areas, visual areas, amygdala, and thalamus. A total of four imaging features were significantly correlated with clinical rating scales in all patients (r=-0.38 to 0.47, P<0.01, after FDR correction). The predictive ability of the random forest classifiers achieved an accuracy of 78.1% in the external sample to identify MwA. Conclusions: The whole-brain connectivity features in our results may serve as connectome-based imaging markers for MwA identification. The alterations of SC and FC strength provide possible evidence in further understanding the heterogeneity and mechanism of MwA which may help for patient-specific decision-making.

Hippocampal volume and resting-state functional connectivity on magnetic resonance imaging in patients with Parkinson and depression.

Background: Recent structural and functional imaging studies of depression in Parkinson disease (DPD) have failed to reveal the relevant mechanism, and relatively few studies have been conducted on limbic systems such as the hippocampus. This study thus aimed to gain new insights into the pathogenesis of DPD by detecting the changes in the hippocampal structure and the resting-state functional connectivity (FC) of patients with DPD. Methods: This study included 30 patients with DPD (DPD group), 30 patients with nondepressed Parkinson disease (NDPD; NDPD group), and 30 normal controls (NCs; NC group) with no significant age or gender differences with the DPD group. The Hamilton Depression Rating Scale (HAMD) and three-dimensional T1-weighted imaging and blood oxygen level-dependent imaging data of all patients were collected. The hippocampal volumes were measured using MATLAB software (MathWorks). The correlation between hippocampal volume and the HAMD score in the DPD group was analyzed with Pearson correlation coefficient. The bilateral hippocampi were used as the regions of interest and as the seed points for FC. FC analysis was performed between the preprocessed functional data of the whole brain and the two seed points with Data Processing Assistant for Resting-State and Statistical Parametric Mapping 8 software, respectively. The correlation between FC and HAMD scores in the patients with DPD was determined using partial correlation analysis. Results: Compared with those in the NC group and the NDPD group, the bilateral hippocampal volumes in the DPD group were significantly decreased (P<0.05). There was a negative correlation between the bilateral hippocampal volume and the HAMD score in the DPD group (P<0.05). Compared with that of the NDPD group, the FC of the right hippocampus with the right occipital lobe and left precuneus was reduced in the DPD group. In the DPD group, the FC values of the right hippocampus, right occipital lobe, and left anterior cuneiform lobe were negatively correlated with HAMD scores. Conclusions: The volume of bilateral hippocampi in patients with DPD is significantly decreased and negatively correlated with the severity of depressive disorder. The weakened FC of the right hippocampus to the right occipital lobe and the left precuneus may play an important role in the neurological basis of DPD.

Social robots as effective language tutors for children: empirical evidence from neuroscience.

The aim of the current study was to investigate children's brain responses to robot-assisted language learning. EEG brain signals were collected from 41 Japanese children who learned French vocabularies in two groups; half of the children learned new words from a social robot that narrated a story in French using animations on a computer screen (Robot group) and the other half watched the same animated story on the screen but only with a voiceover narration and without the robot (Display group). To examine brain activation during the learning phase, we extracted EEG functional connectivity (FC) which is defined as the rhythmic synchronization of signals recorded from different brain areas. The results indicated significantly higher global synchronization of brain signals in the theta frequency band in the Robot group during the learning phase. Closer inspection of intra-hemispheric and inter-hemispheric connections revealed that children who learned a new language from the robot experienced a stronger theta-band EEG synchronization in inter-hemispheric connections, which has been previously associated with success in second language learning in the neuroscientific literature. Additionally, using a multiple linear regression analysis, it was found that theta-band FC and group assignment were significant predictors of children's language learning with the Robot group scoring higher in the post-interaction word recognition test. These findings provide novel neuroscientific evidence for the effectiveness of social robots as second language tutors for children.

Abnormal alterations of regional spontaneous neuronal activity and functional connectivity in insomnia patients with difficulty falling asleep: a resting-state fMRI study.

BACKGROUND: Insomnia disorder (ID) seriously affects people's daily life. Difficulty falling asleep is the most commonly reported complaint in patients with ID. However, the mechanism of prolonged sleep latency (SL) is still obscure. The aim of our present study was to investigate the relationship between prolonged SL and alterations in spontaneous neural activity and brain functional connectivity (FC) in ID patients using functional magnetic resonance imaging (fMRI). METHODS: A total of 52 insomniacs with difficulty falling asleep and 30 matched healthy controls (HCs) underwent resting-state fMRI. The amplitude of low-frequency fluctuation (ALFF) was measured and group differences were compared. The peak areas with significantly different ALFF values were identified as the seed regions to calculate FC to the whole brain. SL was assessed by a wrist actigraphy device in ID patients. The Pittsburgh Sleep Quality Index (PSQI), Hamilton Anxiety Rating Scale (HAMA), and Hyperarousal Scale (HAS) were evaluated in both ID patients and HCs. Finally, correlation analyses were performed between the clinical features and FC/ALFF values. RESULTS: ID patients showed higher PSQI, HAMA, HAS scores than HCs. The functional MRI results indicated increased ALFF value in the left insula and right amygdala and decreased ALFF value in the right superior parietal lobe (SPL) in ID patients. The seed-based FC analysis demonstrated increased FC between the left insula and the bilateral precentral gyrus and FC between the right amygdala and the left posterior cingulate cortex (PCC) in patients with ID. Correlation analysis indicated that the increased FC value of the right amygdala-left PCC was positively correlated with SL measured by actigraphy. CONCLUSION: This study revealed abnormal regional spontaneous fluctuations in the right amygdala, left insula, and right SPL, as well as increased FC in the left insula-precentral and right amygdala-left PCC. Moreover, the prolonged SL was positively correlated with the abnormal FC in the right amygdala-left PCC in ID patients. The current study showed the correlation between prolonged SL and the abnormal function of emotion-related brain regions in ID patients, which may contribute to a better understanding of the neural mechanisms underlying difficulty falling asleep in patients with ID. CLINICAL TRIAL REGISTRATION: http://www.chictr.org.cn ., ChiCTR1800015282. Registered on 20th March 2018.

Association of aberrant structural-functional network coupling with cognitive decline in patients with non-dialysis-dependent stage 5 chronic kidney disease.

Background: Cognitive decline exists in the chronic kidney disease (CKD) population and is particularly severe in patients with stage 5 CKD, but the mechanisms underlying this relationship are unclear. Structural-functional coupling, an integrated measure that combines functional and structural networks, offers the possibility of exploring changes in network relationships in patients with stage 5 CKD. This study aimed to investigate the brain network topology and structural-functional coupling characteristics in patients with non-dialysis-dependent stage 5 CKD (CKD 5ND) and the correlation between network changes and cognitive scores. Methods: We prospectively performed diffusion tensor and resting-state functional magnetic resonance (rs-fMRI) imaging on 40 patients with CKD 5ND disease and 47 healthy controls (HCs). Graph theory analysis of functional and structural connectivity (SC) was performed. Small-world properties and network efficiency properties were calculated, including characteristic path length (Lp), clustering coefficient (Cp), normalized clustering coefficient (Gamma), normalized characteristic path length (Lambda), small-worldness (Sigma), global efficiency (Eglob), and local efficiency (Eloc). The SC-functional connectivity (FC) coupling characteristics and the association between Montreal Cognitive Assessment (MoCA) scores and graph-theoretical features were analyzed. Results: For SC, the Sigma (P=0.009), Cp (P=0.01), Eglob (P<0.001), and Eloc (P=0.01) were significantly lower in patients with CKD 5ND than in HCs, while Lp (P<0.001) and Lambda (P<0.001) were significantly higher in the patients than in the HCs. For FC, the Sigma (P=0.008), Gamma (P=0.009), Eglob (P=0.04), and Eloc (P<0.0001) were lower in patients with CKD 5ND than in HCs; however, the Lp (P=0.02) was higher in the patients than in the HCs. SC-SC coupling (P<0.001) was greater in patients with CKD 5ND than in HCs. The structural (Cp, Eloc, Eglob) and functional network parameters (Sigma, Gamma, Eglob) of the patients with CKD 5ND were positively correlated with MoCA scores; however, the Lp of both structural and functional networks was negatively correlated with MoCA scores. Conclusions: All patients with CKD 5ND included in the study exhibited changes in their structural and functional brain network topology closely related to mild cognitive impairment. SC-SC coupling was elevated in the patients compared with that in the controls. This may provide vital information for understanding and revealing the underlying mechanisms of cognitive impairment in patients with CKD 5ND.

Networks extracted from nonlinear fMRI connectivity exhibit unique spatial variation and enhanced sensitivity to differences between individuals with schizophrenia and controls.

Functional magnetic resonance imaging (fMRI) studies often estimate brain intrinsic connectivity networks (ICNs) from temporal relationships between hemodynamic signals using approaches such as independent component analysis (ICA). While ICNs are thought to represent functional sources that play important roles in various psychological phenomena, current approaches have been tailored to identify ICNs that mainly reflect linear statistical relationships. However, the elements comprising neural systems often exhibit remarkably complex nonlinear interactions that may be involved in cognitive operations and altered in psychiatric conditions such as schizophrenia. Consequently, there is a need to develop methods capable of effectively capturing ICNs from measures that are sensitive to nonlinear relationships. Here, we advance a novel approach to estimate ICNs from explicitly nonlinear whole-brain functional connectivity (ENL-wFC) by transforming resting-state fMRI (rsfMRI) data into the connectivity domain, allowing us to capture unique information from distance correlation patterns that would be missed by linear whole-brain functional connectivity (LIN-wFC) analysis. Our findings provide evidence that ICNs commonly extracted from linear (LIN) relationships are also reflected in explicitly nonlinear (ENL) connectivity patterns. ENL ICN estimates exhibit higher reliability and stability, highlighting our approach's ability to effectively quantify ICNs from rsfMRI data. Additionally, we observed a consistent spatial gradient pattern between LIN and ENL ICNs with higher ENL weight in core ICN regions, suggesting that ICN function may be subserved by nonlinear processes concentrated within network centers. We also found that a uniquely identified ENL ICN distinguished individuals with schizophrenia from healthy controls while a uniquely identified LIN ICN did not, emphasizing the valuable complementary information that can be gained by incorporating measures that are sensitive to nonlinearity in future analyses. Moreover, the ENL estimates of ICNs associated with auditory, linguistic, sensorimotor, and self-referential processes exhibit heightened sensitivity towards differentiating between individuals with schizophrenia and controls compared to LIN counterparts, demonstrating the translational value of our approach and of the ENL estimates of ICNs that are frequently reported as disrupted in schizophrenia. In summary, our findings underscore the tremendous potential of connectivity domain ICA and nonlinear information in resolving complex brain phenomena and revolutionizing the landscape of clinical FC analysis.

Alterations of interhemispheric functional homotopic connectivity and corpus callosum microstructure in bulimia nervosa.

Background: Accumulating evidence indicates maladaptive neural information interactions between different brain regions underlie bulimia nervosa (BN). However, little is known about the alterations in interhemispheric communication of BN, which is facilitated by the corpus callosum (CC), the major commissural fiber connecting the two hemispheres. To shed light on the interhemispheric communications in BN, the present study aims to explore alterations of interhemispheric homotopic functional connectivity and the CC microstructure in BN. Methods: Based on magnetic resonance imaging (MRI) data collected from 42 BN patients and 38 healthy controls (HCs), the group differences of voxel-mirrored homotopic connectivity (VMHC) index and CC white matter microstructure were compared. Then brain regions with significant group differences in VMHC were selected as seeds for subsequent functional connectivity (FC) analysis. Seed-based fiber tracking and correlation analysis were used to analyze the relationship between VMHC and CC changes. And correlation analysis was used to reveal the correlation between abnormal imaging variables and the clinical features of BN. Results: Compared with HCs, the BN group showed decreased fractional anisotropy (FA) in middle part of CC (CCMid) and increased VMHC in bilateral orbitofrontal cortex (OFC) and middle temporal gyrus (MTG) [false discovery rate (FDR) correction with a corrected threshold of P<0.05]. Subsequent FC analyses indicated increased FC between left OFC and right OFC, bilateral MTG, left middle occipital gyrus and right precuneus (PCUN); between right OFC and left cerebellum crus II and right PCUN; and between left MTG and right inferior temporal gyrus, right cerebellum lobule VI and right medial superior frontal gyrus (FDR correction with a corrected threshold of P<0.05). The VMHC values of OFC and MTG showed no correlations with FA values of the CCMid and the white fibers between the bilateral OFC and MTG were not through the CCMid. In addition, several regions with abnormal FC had a potential correlation trend with abnormal eating behaviors in BN patients (P<0.05, uncorrected). Conclusions: Aberrant interhemispheric homotopic functional connectivity and CC microstructure were observed in BN, and they may be independent of each other. Regions with aberrant interhemispheric homotopic functional connectivity showed hyperconnectivity with regions related to reward processing, body shape perception, and self-reference.

Identifying canonical and replicable multi-scale intrinsic connectivity networks in 100k+ resting-state fMRI datasets.

Despite the known benefits of data-driven approaches, the lack of approaches for identifying functional neuroimaging patterns that capture both individual variations and inter-subject correspondence limits the clinical utility of rsfMRI and its application to single-subject analyses. Here, using rsfMRI data from over 100k individuals across private and public datasets, we identify replicable multi-spatial-scale canonical intrinsic connectivity network (ICN) templates via the use of multi-model-order independent component analysis (ICA). We also study the feasibility of estimating subject-specific ICNs via spatially constrained ICA. The results show that the subject-level ICN estimations vary as a function of the ICN itself, the data length, and the spatial resolution. In general, large-scale ICNs require less data to achieve specific levels of (within- and between-subject) spatial similarity with their templates. Importantly, increasing data length can reduce an ICN's subject-level specificity, suggesting longer scans may not always be desirable. We also find a positive linear relationship between data length and spatial smoothness (possibly due to averaging over intrinsic dynamics), suggesting studies examining optimized data length should consider spatial smoothness. Finally, consistency in spatial similarity between ICNs estimated using the full data and subsets across different data lengths suggests lower within-subject spatial similarity in shorter data is not wholly defined by lower reliability in ICN estimates, but may be an indication of meaningful brain dynamics which average out as data length increases.

Nucleus accumbens deep brain stimulation improves depressive-like behaviors through BDNF-mediated alterations in brain functional connectivity of dopaminergic pathway.

Major depressive disorder (MDD), a common psychiatric condition, adversely affects patients' moods and quality of life. Despite the development of various treatments, many patients with MDD remain vulnerable and inadequately controlled. Since anhedonia is a feature of depression and there is evidence of leading to metabolic disorder, deep brain stimulation (DBS) to the nucleus accumbens (NAc) might be promising in modulating the dopaminergic pathway. To determine whether NAc-DBS alters glucose metabolism via mitochondrial alteration and neurogenesis and whether these changes increase neural plasticity that improves behavioral functions in a chronic social defeat stress (CSDS) mouse model. The Lab-designed MR-compatible neural probes were implanted in the bilateral NAc of C57BL/6 mice with and without CSDS, followed by DBS or sham stimulation. All animals underwent open-field and sucrose preference testing, and brain resting-state functional MRI analysis. Meanwhile, we checked the placement of neural probes in each mouse by T2 images. By confirming the placement location, mice with incorrect probe placement (the negative control group) showed no significant therapeutic effects in behavioral performance and functional connectivity (FC) after receiving electrical stimulation and were excluded from further analysis. Western blotting, seahorse metabolic analysis, and electron microscopy were further applied for the investigation of NAc-DBS. We found NAc-DBS restored emotional deficits in CSDS-subjected mice. Concurrent with behavioral amelioration, the CSDS DBS-on group exhibited enhanced FC in the dopaminergic pathway with increased expression of BDNF- and NeuN-positive cells increased dopamine D1 receptor, dopamine D2 receptors, and TH in the medial prefrontal cortex, NAc, ventral hippocampus, ventral tegmental area, and amygdala. Increased pAMPK/total AMPK and PGC-1α levels, functions of oxidative phosphorylation, and mitochondrial biogenesis were also observed after NAc-DBS treatment. Our findings demonstrate that NAc-DBS can promote BDNF expression, which alters FC and metabolic profile in the dopaminergic pathway, suggesting a potential strategy for ameliorating emotional processes in individuals with MDD.

Altered connectivity in the cognitive control-related prefrontal cortex in Parkinson's disease with rapid eye movement sleep behavior disorder.

Rapid eye movement sleep behavior disorder (RBD) frequently occurs in Parkinson's disease (PD), however, the exact pathophysiological mechanism is not clear. The prefrontal cortex (PFC), especially ventrolateral prefrontal cortex (VLPFC), dorsolateral prefrontal cortex (DLPFC), and inferior frontal gyrus (IFG) which may play roles by regulating cognitive control processes. The purpose of this study was to investigate whether there is abnormal functional connectivity (FC) maps and volume changes in PD with RBD(PD-RBD). We recruited 20 PD-RBD, 20 PD without RBD (PD-nRBD), and 20 normal controls (NC). We utilized resting-state functional Magnetic Resonance Imaging (rs-MRI) to explore FC changes based on regions of interest (VLPFC, DLPFC, and IFG), and used voxel-based morphology technology to analyze whole-brain volumes by 3D-T1 structural MRI. Except the REM sleep behavioral disorders questionnaire (RBDSQ), the PD-RBD showed lower visuospatial/executive and attention scores than the NC group. The RBDSQ scores were significantly positively correlated with zFC of right DLPFC to bilateral posterior cingulate cortex (PCC) (P = 0.0362, R = 0.4708, AlphaSim corrected) and also significantly positively correlated with zFC of left VLPFC to right inferior temporal (P = 0.0157, R = 0.5323, AlphaSim corrected) in PD-RBD group. Furthermore, abnormal correlations with zFC values were also found in some cognitive subdomains in PD-RBD group. The study may suggest that in PD-RBD patients, the presence of RBD may be related to the abnormal FC of VLPFC and DLPFC, meanwhile, the abnormal FC of DLPFC and IFG may be related to the mechanisms of cognitive impairment.

Functional changes in the salience network of patients with amnesic mild cognitive impairment before and after repetitive transcranial magnetic stimulation.

BACKGROUND: Amnestic mild cognitive impairment (aMCI) is considered to be the prodromal stage of Alzheimer's disease (AD). The precuneus (PCUN) may be an imaging marker for monitoring the progression of AD. Meanwhile, cognitive impairment in AD patients is closely related to functional connectivity (FC) changes in the salience network (SN). We hypothesize that there are specific neuroimaging biomarkers in the SN and that FC changes in aMCI patients after repetitive transcranial magnetic stimulation (rTMS) intervention are associated with cognitive function. The purpose of this study was to first investigate the pattern of functional changes in aMCI patients and healthy controls (HCs) and then compare the functional changes in aMCI patients before and after rTMS targeting to PCUN and its correlation with cognitive function. METHODS: Thirty-six HCs and 61 aMCIs were recruited for our study. Eleven people in the aMCI group received rTMS intervention 5 days a week for 4 weeks. Using the right anterior insula as the seed-of-interest, we first compared FC changes in HC and aMCI patients and then compared cognitive function in aMCI patients before and after rTMS. The above is the functional connection analysis of seed-to-voxel. Moreover, we investigated the FC changes in aMCI patients after rTMS intervention and its correlation with cognitive function. RESULTS: Compared with HC, the aMCI group showed altered FC in bilateral parahippocampal gyrus, bilateral inferior parietal lobule, left middle frontal gyrus, and left middle temporal gyrus. Moreover, rTMS at PCUN improved the cognitive function of aMCI patients, which was related to the altered FC in posterior cerebellar lobes (CPL). CONCLUSIONS: Our findings suggest that rTMS targeting PCUN is a promising, noninvasive approach to ameliorating cognitive dysfunction in aMCI patients, and that this cognitive improvement is accompanied by brain connectivity modulation.

Spatial Smoothing Effect on Group-Level Functional Connectivity during Resting and Task-Based fMRI.

Spatial smoothing is a preprocessing step applied to neuroimaging data to enhance data quality by reducing noise and artifacts. However, selecting an appropriate smoothing kernel size can be challenging as it can lead to undesired alterations in final images and functional connectivity networks. However, there is no sufficient information about the effects of the Gaussian kernel size on group-level results for different cases yet. This study investigates the influence of kernel size on functional connectivity networks and network parameters in whole-brain rs-fMRI and tb-fMRI analyses of healthy adults. The analysis includes {0, 2, 4, 6, 8, 10} mm kernels, commonly used in practical analyses, covering all major brain networks. Graph theoretical measures such as betweenness centrality, global/local efficiency, clustering coefficient, and average path length are examined for each kernel. Additionally, principal component analysis (PCA) and independent component analysis (ICA) parameters, namely kurtosis and skewness, are evaluated for the functional images. The findings demonstrate that kernel size directly affects node connections, resulting in modifications to functional network structures and PCA/ICA parameters. However, network metrics exhibit greater resilience to these changes.