Occipital connectivity networks mediate the neural effects of childhood maltreatment on depressive symptoms in major depressive disorder.

BACKGROUND: Childhood maltreatment (CM) is a well-established risk factor for major depressive disorder (MDD). The neural mechanisms linking childhood maltreatment experiences to changes in brain functional networks and the onset of depression are not fully understood. METHODS: In this study, we enrolled 66 patients with MDD and 31 healthy controls who underwent resting-state fMRI scans and neuropsychological assessments. We employed multivariate linear regression to examine the neural associations of CM and depression, specifically focusing on the bilateral occipital functional connectivity (OFC) networks relevant to MDD. Subsequently, a two-step mediation analysis was conducted to assess whether the OFC network mediated the relationship between CM experiences and the severity of depression. RESULTS: Our study showed that patients with MDD exhibited reduced OFC strength, particularly in the occipito-temporal, parietal, and premotor regions. These reductions were negatively correlated with CM scores and the severity of depression. Notably, the overlapping regions in the bilateral OFC networks, affected by both CM experiences and depressive severity, were primarily observed in the bilateral cuneus, left angular and calcarine, as well as the right middle frontal cortex and superior parietal cortex. Furthermore, the altered strengths of the OFC networks were identified as positive mediators of the impact of CM history on depression symptoms in patients with MDD. CONCLUSION: We have demonstrated that early exposure to CM may increase vulnerability to depression by influencing the brain's network. These findings provide new insights into understanding the pathological mechanism underlying depressive symptoms induced by CM.

Structural Brain Connectivity guided Optimal Contact Selection for STN-DBS.

BACKGROUND: Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective therapy in ameliorating the motor symptoms of Parkinson's disease (PD). However, postoperative optimal contact selection is crucial for achieving the best outcome of STN-DBS surgery, but the process is currently a trial-and-error and time-consuming procedure that relies heavily on surgeons' clinical experience. METHODS: In this study, we propose a structural brain connectivity guided optimal contact selection method for STN-DBS. Firstly, we reconstruct the DBS electrode location and estimate the stimulation range using volumes of tissue activated (VTA) from each DBS contact. Then, we extract the structural connectivity features by concatenating fractional anisotropy (FA) and the number of streamlines (NOS) features of activated regions and the whole brain regions. Finally, we use a convolutional neural network (CNN) with convolutional block attention module (CBAM) to identify the structural connectivity features for the optimal contact selection. RESULTS: We review the data of 800 contacts from 100 patients with Parkinson disease for the experiment. The proposed method achieves promising results, with the average accuracy of 97.63%, average precision of 94.50%, average recall of 94.46% and average specificity of 98.18%, respectively. Our method can provide the suggestion for optimal contact selection. CONCLUSIONS: Our proposed method can improve the efficiency and accuracy of DBS optimal contact selection, reduce the dependence on surgeons' experience, and has the potential to facilitate the development of advanced DBS technology.

An improved linear systems model of hydrothermal isometric tension testing to aid in assessing bone collagen quality: Effects of ribation and type-2 diabetes.

This study sought to further develop and validate a previously proposed physics-based model that maps denaturation kinetics from differential scanning calorimetry (DSC) to the isometric tension generated during hydrothermal isometric tension (HIT) testing of collagenous tissues. The primary objectives of this study were to verify and validate two physics-based model parameters: α, which indicates the amount of instantaneous isometric tension developed per unit of collagen denaturation, and ß, which captures the proportionality between temperature and the generated isometric tension post denaturation initiation. These parameters were used as measures of bone collagen quality, employing data from HIT and DSC testing of human bone collagen from two previous studies. Additionally, given the physical basis of the model, the study aimed to further validate Max.Slope, the rate of change in isometric tensile stress with change in temperature, as an independent measure of collagen network connectivity. Max.Slope has previously been positively correlated with measures of cortical bone fracture resistance. Towards this verification and validation, the hypotheses were a) that α would correlate strongly with HIT denaturation temperature, Td, and the enthalpy of melting (ΔH) from DSC, and b) that ß would correlate positively and strongly with Max.Slope. The model was employed in the analysis of HIT-DSC data from the testing of demineralized bone collagen isolated from cadaveric human femurs in two prior studies. In one study, data were collected from HIT-DSC testing of cortical bone collagen from 74 donors. Among them, 38 had a history of type 2 diabetes +/- chronic kidney disease, while the remaining 36 had no history of T2D again with or without CKD. Cortical bone specimens were extracted from the lateral mid-shaft. The second study involved 15 donor femora, with four cortical bone specimens extracted from each. Of these four, two specimens underwent a 4-week incubation in 0.1 M ribose at 37 °C to induce non-enzymatic ribation and advanced glycation endproducts, while the other two served as non-ribated controls. The examination involved investigating correlations between the model parameters α and ß and various measures, such as Max.Slope, Td, ΔH, age, and duration of type 2 diabetes. The results revealed positive correlations between the model parameter ß and Max.Slope (r = 0.55-0.58). The parameter α was found to be associated with Td, but also sensitive to the shape of the HIT curve around Td resulting in difficulties with variability and interpretation. As a result, while both hypotheses are confirmed, Max.Slope and ß are better indicators of bone collagen quality because they are measures of the connectivity or, more generally, the integrity of the bone collagen network.

Hyperactivation of MEK1 in cortical glutamatergic neurons results in projection axon deficits and aberrant motor learning.

Abnormal Extracellular Regulated Kinase 1/2 (ERK1/2) signaling is linked to multiple neurodevelopmental diseases, especially the RASopathies, which typically exhibit ERK1/2 hyperactivation in neurons and non-neuronal cells. To better understand how excitatory neuron-autonomous ERK1/2 activity regulates forebrain development, we conditionally expressed hyperactive MEK1S217/221E in cortical excitatory neurons. MEK1S217/221E expression led to persistent hyperactivation of ERK1/2 in cortical axons, but not in soma/nuclei. We noted reduced axonal arborization in multiple target domains in mutants and reduced expression of the activity dependent gene, ARC. These changes did not lead to deficits in voluntary locomotion or accelerating rotarod performance. However, skilled motor learning in a single-pellet retrieval task was significantly diminished in these MEK1S217/221E mutants. Restriction of MEK1S217/221E expression to layer V cortical neurons recapitulated axonal outgrowth deficits, but did not effect motor learning. These results suggest that cortical excitatory neuron-autonomous hyperactivation of MEK1 is sufficient to drive deficits in axon outgrowth, which coincide with reduced ARC expression, and deficits in skilled motor learning. Our data indicate that neuron-autonomous decreases in long-range axonal outgrowth may be a key aspect of neuropathogenesis in RASopathies.

Evaluating functional connectivity differences between DBS ON/OFF states in essential tremor.

Deep brain stimulation (DBS) targeting the ventral intermediate (Vim) nucleus of the thalamus is an effective treatment for essential tremor (ET). We studied 15 â€‹ET patients undergoing DBS to a major input/output tract of the Vim, the dentato-rubro-thalamic tract (DRTt), using resting state functional MRI (rsfMRI) to evaluate connectivity differences between DBS ON and OFF and elucidate significant regions most influential in impacting tremor control and/or concomitant gait ataxia. Anatomical/functional 1.5T MRIs were acquired and replicated for each DBS state. Tremor severity and gait ataxia severity were scored with DBS ON at optimal stimulation parameters and immediately upon DBS OFF. Whole brain analysis was performed using dual regression analysis followed by randomized permutation testing for multiple correction comparison. Regions of interest (ROI) analysis was also performed. All 15 patients had tremor improvement between DBS ON/OFF (p â€‹< â€‹0.001). Whole brain analysis revealed significant connectivity changes between states in the left pre-central gyrus and left supplemental motor area. Group analysis of ROIs revealed that, with threshold p â€‹< â€‹0.05, in DBS ON vs. OFF both tremor duration and tremor improvement were significantly correlated to changes in connectivity. A sub-group analysis of patients with greater ataxia had significantly decreased functional connectivity between multiple ROIs in the cortex and cerebellum when DBS was ON compared to OFF. Stimulation of the DRTt and concordant improvement of tremor resulted in connectivity changes seen in multiple regions outside the motor network; when combined with both structural and electrophysiologic connectivity, this may help to serve as a biomarker to improve DBS targeting and possibly predict outcome.

Functional and Effective Connectivity Underlying Semantic Verbal Fluency.

Semantic verbal fluency (SVF) impairment is present in several neurological disorders. Although activation in SVF-related areas has been reported, how these regions are connected and their functional roles in the network remain divergent. We assessed SVF static and dynamic functional connectivity (FC) and effective connectivity in healthy participants using functional magnetic resonance imaging. We observed activation in the inferior frontal (IFG), middle temporal (pMTG) and angular gyri (AG), anterior cingulate (AC), insular cortex, and regions of the superior, middle, and medial frontal gyri (SFG, MFG, MidFG). Our static FC analysis showed a highly interconnected task and resting state network. Increased connectivity of AC with the pMTG and AG was observed for the task. The dynamic FC analysis provided circuits with connections similarly modulated across time and regions related to category identification, language comprehension, word selection and recovery, word generation, inhibition of speaking, speech planning, and articulatory planning of orofacial movements. Finally, the effective connectivity analysis provided a network that best explained our data, starting at the AG and going to the pMTG, from which there was a division between the ventral and dorsal streams. The SFG and MFG regions were connected and modulated by the MidFG, while the inferior regions formed the ventral stream. Therefore, we successfully assessed the SVF network, exploring regions associated with the entire processing, from category identification to word generation. The methodological approach can be helpful for further investigation of the SVF network in neurological disorders.

Toward a mechanistic understanding of the role of error monitoring and memory in social anxiety.

Cognitive models state that social anxiety (SA) involves biased cognitive processing that impacts what is learned and remembered within social situations, leading to the maintenance of SA. Neuroscience work links SA to enhanced error monitoring, reflected in error-related neural responses arising from mediofrontal cortex (MFC). Yet, the role of error monitoring in SA remains unclear, as it is unknown whether error monitoring can drive changes in memory, biasing what is learned or remembered about social situations. Motivated by the longer-term goal of identifying mechanisms implicated in SA, in the current study we developed and validated a novel paradigm for probing the role of error-related MFC theta oscillations (associated with error monitoring) and incidental memory biases in SA. Electroencephalography (EEG) data were collected while participants completed a novel Face-Flanker task, involving presentation of task-unrelated, trial-unique faces behind target/flanker arrows on each trial. A subsequent incidental memory assessment evaluated memory biases for error events. Severity of SA symptoms were associated with greater error-related theta synchrony over MFC, as well as between MFC and sensory cortex. Social anxiety also was positively associated with incidental memory biases for error events. Moreover, greater error-related MFC-sensory theta synchrony during the Face-Flanker predicted subsequent incidental memory biases for error events. Collectively, the results demonstrate the potential of a novel paradigm to elucidate mechanisms underlying relations between error monitoring and SA.

Alterations of brain structural and functional connectivity networks topology and decoupling in pediatric myelin oligodendrocyte glycoprotein antibody-associated disease.

OBJECTIVE: To investigate the alteration in structural and functional connectivity networks (SCN and FCN) as well as their coupling in pediatric myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), and determine if these properties could serve as potential biomarkers for the disease. MATERIALS AND METHODS: In total of 32 children with MOGAD and 30 age- and sex-matched healthy controls (HC) were employed to construct the SCN and FCN, respectively. The graph-theoretical analyses of the global properties, node properties of the 90 brain nodes, and the structural-functional connectivity (SC-FC) coupling of the two networks were performed. The graph-theoretical properties that exhibited significant differences were analyzed using partial correlation analysis in conjunction with the clinical scales, including the expanded disability status scale (EDSS), modified Rankin scale (mRS), and pediatric cerebral performance category (PCPC) of the MOGAD group. Subsequently, a machine learning model was developed to discriminate between MOGAD and the HC group, aiming to explore the potential of these properties as biomarkers. RESULTS: The SCN of the MOGAD group exhibited aberrant global properties, including an increased characteristic path length (Lp) and a decreased global efficiency (Eg), along with reduced nodal properties such as degree centrality (Dc), nodal efficiency (Ne), and local efficiency in multiple nodes. The FCN of the MOGAD group only exhibited decreased Dc, Ne, and betweenness centrality in two nodes of nodal properties. Besides, MOGAD showed a significant decrease in SC-FC coupling compared to the HC group. The analysis of partial correlation revealed significant correlations between several properties and the scales of EDSS and mRS in the MOGAD group. The machine learning method was used to extract six features and establish the model, achieving a classification accuracy of 82.3% for MOGAD. CONCLUSIONS: Pediatric MOGAD showed a more pronounced impairment in the SCN along with decoupling of SC-FC. Both partial correlation analysis and discriminant modeling suggest that alterations in brain network properties have the potential as biomarkers for assessing brain damage in MOGAD.

A predictive study of the efficacy of transcutaneous auricular vagus nerve stimulation in the treatment of major depressive disorder: An fMRI-based machine learning analysis.

BACKGROUND: In order to improve taVNS efficacy, the usage of fMRI to explore the predictive neuroimaging markers would be beneficial for screening the appropriate MDD population before treatment. METHODS: A total of 86 MDD patients were recruited in this study, and all subjects were conducted with the clinical scales and resting-state functional magnetic resonance imaging (fMRI) scan before and after 8 weeks' taVNS treatment. A two-stage feature selection strategy combining Machine Learning and Statistical was used to screen out the critical brain functional connections (FC) that were significantly associated with efficacy prediction, then the efficacy prediction model was constructed for taVNS treating MDD. Finally, the model was validated by separated the responding and non-responding patients. RESULTS: This study showed that taVNS produced promising clinical efficacy in the treatment of mild and moderate MDD. Eleven FCs were selected out and were found to be associated with the cortico-striatal-pallidum-thalamic loop, the hippocampus and cerebellum and the HAMD-17 scores. The prediction model was created based on these FCs for the efficacy prediction of taVNS treatment. The R-square of the conducted regression model for predicting HAMD-17 reduction rate is 0.44, and the AUC for classifying the responding and non-responding patients is 0.856. CONCLUSION: The study demonstrates the validity and feasibility of combining neuroimaging and machine learning techniques to predict the efficacy of taVNS on MDD, and provides an effective solution for personalized and precise treatment for MDD.

Neural activity and connectivity are related to food preference changes induced by food go/no-go training.

Simply withholding a response while viewing an appetizing food, over the course of many presentations (i.e., during food go/no-go training) can modify individuals' food preferences-which could, in turn, promote healthier eating behaviors. However, the neural mechanisms underlying this food go/no-go training-induced change in food preferences are still relatively unclear. We addressed this issue in the present functional magnetic resonance imaging (fMRI) study. To this end, we administered a novel passive viewing task before and after food go/no-go training to 91 participants in the scanner. Participants' food preferences were measured with a binary food choice task. At the behavioral level, we found the expected training effect on food preferences: Participants preferred go over no-go foods following training. At the neural level, we found that changes in food preferences were associated with training-related go vs. no-go differences in activity and functional connectivity, such as less activity in the anterior cingulate cortex and superior frontal gyrus but greater functional connectivity between the superior frontal gyrus and middle occipital gyrus. Critically, Dynamic causal modeling showed that this preference change effect was largely driven by top-down influence from the superior frontal gyrus to the middle occipital gyrus. Together, these findings suggest a neural mechanism of the food go/no-go training effect-namely, that the food-viewing-related interplay between prefrontal regions and visual regions might be related to the food preference change following food go/no-go training.

Abnormal dynamic functional connectivity and topological properties of cerebellar network in male obstructive sleep apnea.

PURPOSE: To investigate dynamic functional connectivity (dFC) within the cerebellar-whole brain network and dynamic topological properties of the cerebellar network in obstructive sleep apnea (OSA) patients. METHODS: Sixty male patients and 60 male healthy controls were included. The sliding window method examined the fluctuations in cerebellum-whole brain dFC and connection strength in OSA. Furthermore, graph theory metrics evaluated the dynamic topological properties of the cerebellar network. Additionally, hidden Markov modeling validated the robustness of the dFC. The correlations between the abovementioned measures and clinical assessments were assessed. RESULTS: Two dynamic network states were characterized. State 2 exhibited a heightened frequency, longer fractional occupancy, and greater mean dwell time in OSA. The cerebellar networks and cerebrocerebellar dFC alterations were mainly located in the default mode network, frontoparietal network, somatomotor network, right cerebellar CrusI/II, and other networks. Global properties indicated aberrant cerebellar topology in OSA. Dynamic properties were correlated with clinical indicators primarily on emotion, cognition, and sleep. CONCLUSION: Abnormal dFC in male OSA may indicate an imbalance between the integration and segregation of brain networks, concurrent with global topological alterations. Abnormal default mode network interactions with high-order and low-level cognitive networks, disrupting their coordination, may impair the regulation of cognitive, emotional, and sleep functions in OSA.

Subanaesthetic ketamine suppresses locus coeruleus mediated alertness effects - a 7T fMRI study.

BACKGROUND: The NMDA antagonist s-ketamine is gaining increasing use as a rapid-acting antidepressant, although its exact mechanisms of action are still unknown. In this study, we investigated ketamine in respect to its properties towards central noradrenergic mechanisms and how they influence alertness behavior. METHODS: We investigated the influence of s-ketamine on the locus coeruleus (LC) brain network in a placebo controlled, cross-over, 7T functional, pharma- cological MRI study in thirty-five healthy male participants (25.1±4.2 years) in conjunction with the attention network task, to measure LC-related alert- ness behavioral changes. RESULTS: We could show that acute disruption of the LC alertness network to the thalamus by ketamine is related to a behavioral alertness reduction. CONCLUSION: The results shed new light on the neural correlates of ketamine beyond the glutamatergic system and underpin a new concept of how it may unfold its antidepressant effects.

Structural and functional neural patterns among sub-threshold bulimia nervosa: Abnormalities in dorsolateral prefrontal cortex and orbitofrontal cortex.

BACKGROUND: Disordered eating behaviors are prevalent among youngsters and highly associated with dysfunction in neurocognitive systems. We aimed to identify the potential changes in individuals with bulimia symptoms (sub-BN) to generate insights to understand developmental pathophysiology of bulimia nervosa. METHODS: We investigated group differences in terms of degree centrality (DC) and gray matter volume (GMV) among 145 undergraduates with bulimia symptoms and 140 matched control undergraduates, with the secondary analysis of the whole brain connectivity in these regions of interest showing differences in static functional connectivity (FC). RESULTS: The sub-BN group exhibited abnormalities of the right dorsolateral prefrontal cortex and right orbitofrontal cortex in both GMV and DC, and displayed decreased FC between these regions and the precuneus. We also observed that sub-BN presented with reduced FC between the calcarine and superior temporal gyrus, middle temporal gyrus and inferior parietal gyrus. Additionally, brain-behavioral associations suggest a distinct relationship between these FCs and psychopathological symptoms in sub-BN group. CONCLUSIONS: Our study demonstrated that individuals with bulimia symptoms present with aberrant neural patterns that mainly involved in cognitive control and reward processing, as well as attentional and self-referential processing, which could provide important insights into the pathology of BN.

Comparative analysis of resting-state EEG functional connectivity in depression and obsessive-compulsive disorder.

Major depressive disorder (MDD) and obsessive-compulsive disorder (OCD) are psychiatric disorders that often co-occur. We aimed to investigate whether their high comorbidity could be traced not only by clinical manifestations, but also at the level of functional brain activity. In this paper, we examined the differences in functional connectivity (FC) at the whole-brain level and within the default mode network (DMN). Resting-state EEG was obtained from 43 controls, 26 OCD patients, and 34 MDD patients. FC was analyzed between 68 cortical sources, and between-group differences in the 4-30 Hz range were assessed via the Network Based Statistic method. The strength of DMN intra-connectivity was compared between groups in the theta, alpha and beta frequency bands. A cluster of 67 connections distinguished the OCD, MDD and control groups. The majority of the connections, 8 of which correlated with depressive symptom severity, were found to be weaker in the clinical groups. Only 3 connections differed between the clinical groups, and one of them correlated with OCD severity. The DMN strength was reduced in the clinical groups in the alpha and beta bands. It can be concluded that the high comorbidity of OCD and MDD can be traced at the level of FC.

Effective Brain Connectivity Related to Non-Painful Thermal Stimuli Using EEG.

Understanding the brain response to thermal stimuli is crucial in the sensory experience. This study focuses on non-painful thermal stimuli, which are sensations induced by temperature changes without causing discomfort. These stimuli are transmitted to the central nervous system through specific nerve fibers and are processed in various regions of the brain, including the insular cortex, the prefrontal cortex, and anterior cingulate cortex. Despite the prevalence of studies on painful stimuli, non-painful thermal stimuli have been less explored. This research aims to bridge this gap by investigating brain functional connectivity during the perception of non-painful warm and cold stimuli using electroencephalography (EEG) and the partial directed coherence technique (PDC). Our results demonstrate a clear contrast in the direction of information flow between warm and cold stimuli, particularly in the theta and alpha frequency bands, mainly in frontal and temporal regions. The use of PDC highlights the complexity of brain connectivity during these stimuli and reinforces the existence of different pathways in the brain to process different types of non-painful warm and cold stimuli.

Enhancing social behavior in an autism spectrum disorder mouse model: investigating the underlying mechanisms of Lactiplantibacillus plantarum intervention.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder affecting over 1% of the global population. Individuals with ASD often exhibit complex behavioral conditions, including significant social difficulties and repetitive behaviors. Moreover, ASD often co-occurs with several other conditions, including intellectual disabilities and anxiety disorders. The etiology of ASD remains largely unknown owing to its complex genetic variations and associated environmental risks. Ultimately, this poses a fundamental challenge for the development of effective ASD treatment strategies. Previously, we demonstrated that daily supplementation with the probiotic Lactiplantibacillus plantarum PS128 (PS128) alleviates ASD symptoms in children. However, the mechanism underlying this improvement in ASD-associated behaviors remains unclear. Here, we used a well-established ASD mouse model, induced by prenatal exposure to valproic acid (VPA), to study the physiological roles of PS128 in vivo. Overall, we showed that PS128 selectively ameliorates behavioral abnormalities in social and spatial memory in VPA-induced ASD mice. Morphological examination of dendritic architecture further revealed that PS128 facilitated the restoration of dendritic arborization and spine density in the hippocampus and prefrontal cortex of ASD mice. Notably, PS128 was crucial for restoring oxytocin levels in the paraventricular nucleus and oxytocin receptor signaling in the hippocampus. Moreover, PS128 alters the gut microbiota composition and increases the abundance of Bifidobacterium spp. and PS128-induced changes in Bifidobacterium abundance positively correlated with PS128-induced behavioral improvements. Together, our results show that PS128 treatment can effectively ameliorate ASD-associated behaviors and reinstate oxytocin levels in VPA-induced mice, thereby providing a promising strategy for the future development of ASD therapeutics.

Cross-Frequency Coupling as a Biomarker for Early Stroke Recovery.

BACKGROUND: The application of neuroimaging-based biomarkers in stroke has enriched our understanding of post-stroke recovery mechanisms, including alterations in functional connectivity based on synchronous oscillatory activity across various cortical regions. Phase-amplitude coupling, a type of cross-frequency coupling, may provide additional mechanistic insight. OBJECTIVE: To determine how the phase of prefrontal cortex delta (1-3 Hz) oscillatory activity mediates the amplitude of motor cortex beta (13-20 Hz) oscillations in individual's early post-stroke. METHODS: Participants admitted to an inpatient rehabilitation facility completed resting and task-based EEG recordings and motor assessments around the time of admission and discharge along with structural neuroimaging. Unimpaired controls completed EEG procedures during a single visit. Mixed-effects linear models were performed to assess within- and between-group differences in delta-beta prefrontomotor coupling. Associations between coupling and motor status and injury were also determined. RESULTS: Thirty individuals with stroke and 17 unimpaired controls participated. Coupling was greater during task versus rest conditions for all participants. Though coupling during affected extremity task performance decreased during hospitalization, coupling remained elevated at discharge compared to controls. Greater baseline coupling was associated with better motor status at admission and discharge and positively related to motor recovery. Coupling demonstrated both positive and negative associations with injury involving measures of lesion volume and overlap injury to anterior thalamic radiation, respectively. CONCLUSIONS: This work highlights the utility of prefrontomotor cross-frequency coupling as a potential motor status and recovery biomarker in stroke. The frequency- and region-specific neurocircuitry featured in this work may also facilitate novel treatment strategies in stroke.

Subcortical tau is linked to hypoperfusion in connected cortical regions in 4-repeat tauopathies.

4-repeat (4R) tauopathies are neurodegenerative diseases characterized by cerebral accumulation of 4R tau pathology. The most prominent 4R-tauopathies are progressive-supranuclear-palsy (PSP) and corticobasal-degeneration (CBD) characterized by subcortical tau accumulation and cortical neuronal dysfunction, as shown by PET-assessed hypoperfusion and glucose hypometabolism. Yet, there is a spatial mismatch between subcortical tau deposition patterns and cortical neuronal dysfunction, and it is unclear how these two pathological brain changes are interrelated. Here, we hypothesized that subcortical tau pathology induces remote neuronal dysfunction in functionally connected cortical regions to test a pathophysiological model that mechanistically links subcortical tau accumulation to cortical neuronal dysfunction in 4R tauopathies. We included 51 Aß-negative patients with clinically diagnosed PSP variants (n=26) or Corticobasal Syndrome (CBS; n=25) who underwent structural MRI and 18F-PI-2620 tau-PET. 18F-PI-2620 tau-PET was recorded using a dynamic one-stop-shop acquisition protocol, to determine an early 0.5-2.5 min post-tracer-injection perfusion window for assessing cortical neuronal dysfunction, as well as a 20-40 min post-tracer-injection window to determine 4R-tau load. Perfusion-PET (i.e. early-window) was assessed in 200 cortical regions, and tau-PET was assessed in 32 subcortical regions of established functional brain atlasses. We determined tau epicenters as subcortical regions with highest 18F-PI-2620 tau-PET signal and assessed the connectivity of tau epicenters to cortical ROIs using a resting-state fMRI-based functional connectivity template derived from 69 healthy elderly controls from the ADNI cohort. Using linear regression, we assessed whether i) higher subcortical tau-PET was associated with reduced cortical perfusion and ii) whether cortical perfusion reductions were observed preferentially in regions closely connected to subcortical tau epicenters. As hypothesized, higher subcortical tau-PET was associated with overall lower cortical perfusion, which remained consistent when controlling for cortical tau-PET. Using group-average and subject-level PET data, we found that the seed-based connectivity pattern of subcortical tau epicenters aligned with cortical perfusion patterns, where cortical regions that were more closely connected to the tau epicenter showed lower perfusion. Together, subcortical tau-accumulation is associated with remote perfusion reductions indicative of neuronal dysfunction in functionally connected cortical regions in 4R-tauopathies. This suggests that subcortical tau pathology may induce cortical dysfunction, which may contribute to clinical disease manifestation and clinical heterogeneity.

Sex differences in aberrant functional connectivity of three core networks and subcortical networks in medication-free adolescent-onset major depressive disorder.

Major depressive disorder demonstrated sex differences in prevalence and symptoms, which were more pronounced during adolescence. Yet, research on sex-specific brain network characteristics in adolescent-onset major depressive disorder remains limited. This study investigated sex-specific and nonspecific alterations in resting-state functional connectivity of three core networks (frontoparietal network, salience network, and default mode network) and subcortical networks in adolescent-onset major depressive disorder, using seed-based resting-state functional connectivity in 50 medication-free patients with adolescent-onset major depressive disorder and 56 healthy controls. Irrespective of sex, compared with healthy controls, adolescent-onset major depressive disorder patients showed hypoconnectivity between bilateral hippocampus and right superior temporal gyrus (default mode network). More importantly, we further found that females with adolescent-onset major depressive disorder exhibited hypoconnectivity within the default mode network (medial prefrontal cortex), and between the subcortical regions (i.e. amygdala, striatum, and thalamus) with the default mode network (angular gyrus and posterior cingulate cortex) and the frontoparietal network (dorsal prefrontal cortex), while the opposite patterns of resting-state functional connectivity alterations were observed in males with adolescent-onset major depressive disorder, relative to their sex-matched healthy controls. Moreover, several sex-specific resting-state functional connectivity changes were correlated with age of onset, sleep disturbance, and anxiety in adolescent-onset major depressive disorder with different sex. These findings suggested that these sex-specific resting-state functional connectivity alterations may reflect the differences in brain development or processes related to early illness onset, underscoring the necessity for sex-tailored diagnostic and therapeutic approaches in adolescent-onset major depressive disorder.