Most recent paper

Combined Cognitive Training and Vortioxetine Mitigates Age-Related Declines in Functional Brain Network Integrity

Sat, 02/04/2023 - 19:00

Am J Geriatr Psychiatry. 2023 Jan 14:S1064-7481(23)00005-2. doi: 10.1016/j.jagp.2023.01.004. Online ahead of print.


OBJECTIVE: Age-related cognitive decline is common and potentially modifiable with cognitive training. Combining cognitive training with pro-cognitive medication offers an opportunity to modify brain networks to mitigate age-related cognitive decline. We tested the hypothesis that the efficacy of cognitive training could be amplified by combining it with vortioxetine, a pro-cognitive and pro-neuroplastic multimodal antidepressant.

METHODS: We evaluated the effects of 6 months of computerized cognitive training plus vortioxetine (versus placebo) on resting state functional connectivity in older adults (age 65+) with age-related cognitive decline. We first evaluated the association of functional connectivity with age and cognitive performance (N = 66). Then we compared the effects of vortioxetine plus cognitive training versus placebo plus cognitive training on connectivity changes over the training period (n = 20).

RESULTS: At baseline, greater age was significantly associated with lower within-network strength and network segregation, and poorer cognitive function. Cognitive training plus vortioxetine over 6 months positively impacted the relationship between age to mean network segregation. These effects were not observed in the placebo group. In contrast, vortioxetine did not modify the relationship of age to change in mean within-network strength. Exploratory analyses identified the cingulo-opercular network as the network most affected by cognitive training plus vortioxetine.

CONCLUSION: This preliminary study provides evidence that combining cognitive training with pro-cognitive medication may modulate the effects of aging on functional brain networks. Results indicate that for older adults experiencing age-related cognitive decline, vortioxetine has a potentially beneficial effect on the correspondence between aging and functional brain network segregation. These results await replication in a larger sample.

PMID:36739247 | DOI:10.1016/j.jagp.2023.01.004

CDKL5 sculpts functional callosal connectivity to promote cognitive flexibility

Fri, 02/03/2023 - 19:00

Mol Psychiatry. 2023 Feb 3. doi: 10.1038/s41380-023-01962-y. Online ahead of print.


Functional and structural connectivity alterations in short- and long-range projections have been reported across neurodevelopmental disorders (NDD). Interhemispheric callosal projection neurons (CPN) represent one of the major long-range projections in the brain, which are particularly important for higher-order cognitive function and flexibility. However, whether a causal relationship exists between interhemispheric connectivity alterations and cognitive deficits in NDD remains elusive. Here, we focused on CDKL5 Deficiency Disorder (CDD), a severe neurodevelopmental disorder caused by mutations in the X-linked Cyclin-dependent kinase-like 5 (CDKL5) gene. We found an increase in homotopic interhemispheric connectivity and functional hyperconnectivity across higher cognitive areas in adult male and female CDKL5-deficient mice by resting-state functional MRI (rs-fMRI) analysis. This was accompanied by an increase in the number of callosal synaptic inputs but decrease in local synaptic connectivity in the cingulate cortex of juvenile CDKL5-deficient mice, suggesting an impairment in excitatory synapse development and a differential role of CDKL5 across excitatory neuron subtypes. These deficits were associated with significant cognitive impairments in CDKL5 KO mice. Selective deletion of CDKL5 in the largest subtype of CPN likewise resulted in an increase of functional callosal inputs, without however significantly altering intracortical cingulate networks. Notably, such callosal-specific changes were sufficient to cause cognitive deficits. Finally, when CDKL5 was selectively re-expressed only in this CPN subtype, in otherwise CDKL5-deficient mice, it was sufficient to prevent the cognitive impairments of CDKL5 mutants. Together, these results reveal a novel role of CDKL5 by demonstrating that it is both necessary and sufficient for proper CPN connectivity and cognitive function and flexibility, and further validates a causal relationship between CPN dysfunction and cognitive impairment in a model of NDD.

PMID:36737483 | DOI:10.1038/s41380-023-01962-y

Characterising stationary and dynamic effective connectivity changes in the motor network during and after tDCS

Fri, 02/03/2023 - 19:00

Neuroimage. 2023 Feb 1:119915. doi: 10.1016/j.neuroimage.2023.119915. Online ahead of print.


The exact mechanisms behind the effects of transcranial direct current stimulation (tDCS) at a network level are still poorly understood, with most studies to date focusing on local (cortical) effects and changes in motor-evoked potentials or BOLD signal. Here, we explored stationary and dynamic effective connectivity across the motor network at rest in two experiments where we applied tDCS over the primary motor cortex (M1-tDCS) or the cerebellum (cb-tDCS) respectively. Two cohorts of healthy volunteers (n = 21 and n = 22) received anodal, cathodal, and sham tDCS sessions (counterbalanced) during 20 minutes of resting-state functional magnetic resonance imaging (fMRI). We used spectral Dynamic Causal Modelling (DCM) and hierarchical Parametrical Empirical Bayes (PEB) to analyse data after (compared to a pre-tDCS baseline) and during stimulation. We also implemented a novel dynamic (sliding windows) DCM/PEB approach to model the nature of network reorganisation across time. In both experiments we found widespread effects of tDCS that extended beyond the targeted area and modulated effective connectivity between cortex, thalamus, and cerebellum. These changes were characterised by unique nonlinear temporal fingerprints across connections and polarities. Our results support growing research challenging the classic notion of anodal and cathodal tDCS as excitatory and inhibitory respectively, as well as the idea of a cumulative effect of tDCS over time. Instead, they described a rich set of changes with specific spatial and temporal patterns. Our work provides a starting point for advancing our understanding of network-level tDCS effects and may guide future work to optimise its cognitive and clinical applications.

PMID:36736717 | DOI:10.1016/j.neuroimage.2023.119915

Exploring neural activity in inflammatory bowel diseases using functional connectivity and DKI-fMRI fusion

Fri, 02/03/2023 - 19:00

Behav Brain Res. 2023 Jan 31:114325. doi: 10.1016/j.bbr.2023.114325. Online ahead of print.


Although MRI has made considerable progress in Inflammatory bowel disease (IBD), most studies have concentrated on data information from a single modality, and a better understanding of the interplay between brain function and structure, as well as appropriate clinical aids to diagnosis, is required. We calculated functional connectivity through fMRI time series using resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion kurtosis imaging (DKI) data from 27 IBD patients and 29 healthy controls. Through the DKI data of each subject, its unique structure map is obtained, and the relevant indicators are projected onto the structure map corresponding to each subject by using the graph Fourier transform in the grasp signal processing (GSP) technology. After the features are optimized, a classical support vector machine is used to classify the features. IBD patients have altered functional connectivity in the default mode network (DMN) and subcortical network (SCN). At the same time, compared with the traditional brain network analysis, in the test of some indicators, the average classification accuracy produced by the framework method is 12.73% higher than that of the traditional analysis method. This paper found that the brain network structure of IBD patients in DMN and SCN has changed. Simultaneously, the application of GSP technology to fuse functional information and structural information is superior to the traditional framework in classification, providing a new perspective for subsequent clinical auxiliary diagnosis.

PMID:36736668 | DOI:10.1016/j.bbr.2023.114325

Irritability in early to middle childhood: Cross-sectional and longitudinal associations with resting state amygdala and ventral striatum connectivity

Fri, 02/03/2023 - 19:00

Dev Cogn Neurosci. 2023 Feb 1;60:101206. doi: 10.1016/j.dcn.2023.101206. Online ahead of print.


BACKGROUND: Irritability is a common symptom that may affect children's brain development. This study aims to (1) characterize age-dependent and age-independent neural correlates of irritability in a sample of 4-8 year old children, and (2) examine early irritability as a predictor of change in brain connectivity over time.

METHODS: Typically developing children, ages 4-8 years, with varying levels of irritability were included. Resting state fMRI and parent-rated irritability (via Child Behavior Checklist; CBCL) were collected at up to three time points, resulting in a cross-sectional sample at baseline (N = 176, M = 6.27, SD = 1.49), and two subsamples consisting of children who were either 4 or 6 years old at baseline that were followed longitudinally for two additional timepoints, one- and two-years post-baseline. That is, a "younger" cohort (age 4 at baseline, n = 34, M age = 4.44, SD = 0.25) and an "older" cohort (age 6 at baseline, n = 29, M age = 6.50, SD = 0.30). Across our exploratory analyses, we examined how irritability related to seed-based intrinsic connectivity via whole-brain connectivity ANCOVAs using the left and right amygdala, and left and right ventral striatum as seed regions.

RESULTS: Cross-sectionally, higher levels of irritability were associated with greater amygdala connectivity with the posterior cingulate, controlling for child age. No age-dependent effects were observed in the cross-sectional analyses. Longitudinal analyses in the younger cohort revealed that early higher vs. lower levels of irritability, controlling for later irritability, were associated with decreases in amygdala and ventral striatum connectivity with multiple frontal and parietal regions over time. There were no significant findings in the older cohort.

CONCLUSIONS: Findings suggest that irritability is related to altered neural connectivity during rest regardless of age in early to middle childhood and that early childhood irritability may be linked to altered changes in neural connectivity over time. Understanding how childhood irritability interacts with neural processes can inform pathophysiological models of pediatric irritability and the development of targeted mechanistic interventions.

PMID:36736018 | DOI:10.1016/j.dcn.2023.101206

LSD-induced increase of Ising temperature and algorithmic complexity of brain dynamics

Fri, 02/03/2023 - 19:00

PLoS Comput Biol. 2023 Feb 3;19(2):e1010811. doi: 10.1371/journal.pcbi.1010811. Online ahead of print.


A topic of growing interest in computational neuroscience is the discovery of fundamental principles underlying global dynamics and the self-organization of the brain. In particular, the notion that the brain operates near criticality has gained considerable support, and recent work has shown that the dynamics of different brain states may be modeled by pairwise maximum entropy Ising models at various distances from a phase transition, i.e., from criticality. Here we aim to characterize two brain states (psychedelics-induced and placebo) as captured by functional magnetic resonance imaging (fMRI), with features derived from the Ising spin model formalism (system temperature, critical point, susceptibility) and from algorithmic complexity. We hypothesized, along the lines of the entropic brain hypothesis, that psychedelics drive brain dynamics into a more disordered state at a higher Ising temperature and increased complexity. We analyze resting state blood-oxygen-level-dependent (BOLD) fMRI data collected in an earlier study from fifteen subjects in a control condition (placebo) and during ingestion of lysergic acid diethylamide (LSD). Working with the automated anatomical labeling (AAL) brain parcellation, we first create "archetype" Ising models representative of the entire dataset (global) and of the data in each condition. Remarkably, we find that such archetypes exhibit a strong correlation with an average structural connectome template obtained from dMRI (r = 0.6). We compare the archetypes from the two conditions and find that the Ising connectivity in the LSD condition is lower than the placebo one, especially in homotopic links (interhemispheric connectivity), reflecting a significant decrease of homotopic functional connectivity in the LSD condition. The global archetype is then personalized for each individual and condition by adjusting the system temperature. The resulting temperatures are all near but above the critical point of the model in the paramagnetic (disordered) phase. The individualized Ising temperatures are higher in the LSD condition than the placebo condition (p = 9 × 10-5). Next, we estimate the Lempel-Ziv-Welch (LZW) complexity of the binarized BOLD data and the synthetic data generated with the individualized model using the Metropolis algorithm for each participant and condition. The LZW complexity computed from experimental data reveals a weak statistical relationship with condition (p = 0.04 one-tailed Wilcoxon test) and none with Ising temperature (r(13) = 0.13, p = 0.65), presumably because of the limited length of the BOLD time series. Similarly, we explore complexity using the block decomposition method (BDM), a more advanced method for estimating algorithmic complexity. The BDM complexity of the experimental data displays a significant correlation with Ising temperature (r(13) = 0.56, p = 0.03) and a weak but significant correlation with condition (p = 0.04, one-tailed Wilcoxon test). This study suggests that the effects of LSD increase the complexity of brain dynamics by loosening interhemispheric connectivity-especially homotopic links. In agreement with earlier work using the Ising formalism with BOLD data, we find the brain state in the placebo condition is already above the critical point, with LSD resulting in a shift further away from criticality into a more disordered state.

PMID:36735751 | DOI:10.1371/journal.pcbi.1010811

SDI-118, a novel procognitive SV2A modulator: First-in-human randomized controlled trial including PET/fMRI assessment of target engagement

Fri, 02/03/2023 - 19:00

Front Pharmacol. 2023 Jan 17;13:1066447. doi: 10.3389/fphar.2022.1066447. eCollection 2022.


Background: Current treatments for progressive neurodegenerative disorders characterized by cognitive impairment either have limited efficacy or are lacking altogether. SDI-118 is a small molecule which modulates the activity of synaptic vesicle glycoprotein 2A (SV2A) in the brain and shows cognitive enhancing effects in a range of animal models of cognitive deficit. Methods: This first-in-human study evaluated safety, tolerability, and pharmacokinetics/pharmacodynamics of SDI-118 in single ascending oral doses up to 80 mg administered to 32 healthy male subjects. Brain target occupancy was measured in eight subjects using positron emission tomography with PET-ligand [11C]-UCB-J. Food effect was assessed in seven subjects. Mood state was regularly evaluated using standardized questionnaires, and resting state fMRI data were analyzed as exploratory objectives. Key Results: At all doses tested, SDI-118 was well tolerated and appeared safe. Adverse events were mainly dizziness, hypersomnia, and somnolence. All were mild in intensity and increased in frequency with increasing administered dose. No dose-limiting adverse reactions were observed at any dose. SDI-118 displayed a linear pharmacokinetic profile with no significant food effect. Brain penetration and target engagement were demonstrated by a dose-proportional SV2A occupancy. Conclusion: Single oral doses of SDI-118 up to 80 mg were very well tolerated in healthy male subjects. Dose-proportional SV2A occupancy in the brain was demonstrated with brain imaging. Adverse effects in humans mainly occurred in higher dose ranges, with high occupancy levels, and were all mild and self-limiting. These data support further clinical exploration of the compound in patients with cognitive disorders. Clinical Trial Registration:, identifier NCT05486195.

PMID:36733374 | PMC:PMC9887116 | DOI:10.3389/fphar.2022.1066447

Characteristic cortico-cortical connection profile of human precuneus revealed by probabilistic tractography

Thu, 02/02/2023 - 19:00

Sci Rep. 2023 Feb 2;13(1):1936. doi: 10.1038/s41598-023-29251-2.


It is generally hypothesized that functional connectivity (FC) reflects the underlying structural connectivity (SC). The precuneus is associated with highly integrated cognitive functions. However, our understanding of the structural connections that could underlie them is limited. This study aimed to characterize the cortico-cortical connections by probabilistic tractography. The precuneus corresponds to the five cortical areas (7Am, PCV, 7Pm, 7m, POS2) on the HCP MMP atlas. We first conducted the atlas-based probabilistic tractography. The anterior part (7Am) was strongly connected to the sensorimotor region. The dorsal part (7Am, 7Pm) was highly connected with the adjacent parietal and temporal cortex, while the ventral part (PCV, 7m) showed strong connections with the adjacent posterior cingulate and medial prefrontal cortex. The most posterior part (POS2) was explicitly connected to the visual cortex. In addition, there was a correlation between SC and resting-state fMRI connectivity (Spearman's rank correlation coefficient = 0.322 ± 0.019, p < 0.05 corrected at subject level). Collectively, the current study revealed the characteristic connectional profile of precuneus, which could shed light on the structural heterogeneity for the future functional analyses.

PMID:36732604 | DOI:10.1038/s41598-023-29251-2

Individualized fMRI connectivity defines signatures of antidepressant and placebo responses in major depression

Thu, 02/02/2023 - 19:00

Mol Psychiatry. 2023 Feb 2. doi: 10.1038/s41380-023-01958-8. Online ahead of print.


Though sertraline is commonly prescribed in patients with major depressive disorder (MDD), its superiority over placebo is only marginal. This is in part due to the neurobiological heterogeneity of the individuals. Characterizing individual-unique functional architecture of the brain may help better dissect the heterogeneity, thereby defining treatment-predictive signatures to guide personalized medication. In this study, we investigate whether individualized brain functional connectivity (FC) can define more predictable signatures of antidepressant and placebo treatment in MDD. The data used in the present work were collected by the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study. Patients (N = 296) were randomly assigned to antidepressant sertraline or placebo double-blind treatment for 8 weeks. The whole-brain FC networks were constructed from pre-treatment resting-state functional magnetic resonance imaging (rs-fMRI). Then, FC was individualized by removing the common components extracted from the raw baseline FC to train regression-based connectivity predictive models. With individualized FC features, the established prediction models successfully identified signatures that explained 22% variance for the sertraline group and 31% variance for the placebo group in predicting HAMD17 change. Compared with the raw FC-based models, the individualized FC-defined signatures significantly improved the prediction performance, as confirmed by cross-validation. For sertraline treatment, predictive FC metrics were predominantly located in the left middle temporal cortex and right insula. For placebo, predictive FC metrics were primarily located in the bilateral cingulate cortex and left superior temporal cortex. Our findings demonstrated that through the removal of common FC components, individualization of FC metrics enhanced the prediction performance compared to raw FC. Associated with previous MDD clinical studies, our identified predictive biomarkers provided new insights into the neuropathology of antidepressant and placebo treatment.

PMID:36732585 | DOI:10.1038/s41380-023-01958-8


Thu, 02/02/2023 - 19:00

J Neurosci. 2023 Jan 27:JN-RM-1312-22. doi: 10.1523/JNEUROSCI.1312-22.2022. Online ahead of print.


Healthy brain dynamics can be understood as the emergence of a complex system far from thermodynamic equilibrium. Brain dynamics are temporally irreversible and thus establish a preferred direction in time (i.e., arrow of time). However, little is known about how the time-reversal symmetry of spontaneous brain activity is affected by Alzheimer's disease (AD). We hypothesized that the level of irreversibility would be compromised in AD, signaling a fundamental shift in the collective properties of brain activity towards equilibrium dynamics. We investigated the irreversibility from resting-state fMRI and EEG data in male and female human patients with AD and elderly healthy control subjects (HC). We quantified the level of irreversibility and, thus, proximity to non-equilibrium dynamics by comparing forward and backward timeseries through time-shifted correlations. AD was associated with a breakdown of temporal irreversibility at the global, local, and network levels and at multiple oscillatory frequency bands. At the local level, temporoparietal and frontal regions were affected by AD. The limbic, frontoparietal, default mode, and salience networks were the most compromised at the network level. The temporal reversibility was associated with cognitive decline in AD and grey matter volume in HC. The irreversibility of brain dynamics provided higher accuracy and more distinctive information than classical neurocognitive measures when differentiating AD from controls. Findings were validated using an out-of-sample cohort. Present results offer new evidence regarding pathophysiological links between the entropy generation rate of brain dynamics and the clinical presentation of AD, opening new avenues for dementia characterization at different levels.SIGNIFICANCE STATEMENT:By assessing the irreversibility of large-scale dynamics across multiple brain signals, we provide a precise signature capable of distinguishing Alzheimer's disease (AD) at the global, local, and network levels and different oscillatory regimes. Irreversibility of limbic, frontoparietal, default mode, and salience networks was the most compromised by AD in comparison to more sensory-motor networks. Moreover, the time-irreversibility properties associated with cognitive decline and atrophy outperformed and complemented classical neurocognitive markers of AD in predictive classification performance. Findings were generalized and replicated with an out-of-sample validation procedure. We provide novel multilevel evidence of reduced irreversibility in AD brain dynamics that have the potential to open new avenues for understating neurodegeneration in terms of the temporal asymmetry of brain dynamics.

PMID:36732071 | DOI:10.1523/JNEUROSCI.1312-22.2022

Multiscale functional connectivity patterns of the aging brain learned from harmonized rsfMRI data of the multi-cohort iSTAGING study

Thu, 02/02/2023 - 19:00

Neuroimage. 2023 Jan 30:119911. doi: 10.1016/j.neuroimage.2023.119911. Online ahead of print.


To learn multiscale functional connectivity patterns of the aging brain, we built a brain age prediction model of functional connectivity measures at seven scales on a large fMRI dataset, consisting of resting-state fMRI scans of 4186 individuals with a wide age range (22 to 97 years, with an average of 63) from five cohorts. We computed multiscale functional connectivity measures of individual subjects using a personalized functional network computational method, harmonized the functional connectivity measures of subjects from multiple datasets in order to build a functional brain age model, and finally evaluated how functional brain age gap correlated with cognitive measures of individual subjects. Our study has revealed that functional connectivity measures at multiple scales were more informative than those at any single scale for the brain age prediction, the data harmonization significantly improved the brain age prediction performance, and harmonization in the tangent space worked better than in the original space. Moreover, brain age gap scores of individual subjects derived from the brain age prediction model were significantly correlated with clinical and cognitive measures. Overall, these results demonstrated that multiscale functional connectivity patterns learned from a large-scale multi-site rsfMRI dataset were informative for characterizing the aging brain and the derived brain age gap was associated with cognitive and clinical measures.

PMID:36731813 | DOI:10.1016/j.neuroimage.2023.119911

Aberrant Spontaneous Brain Activity and its Association with Cognitive Function in Non-Obese Nonalcoholic Fatty Liver Disease: A Resting-State fMRI Study

Wed, 02/01/2023 - 19:00

J Integr Neurosci. 2023 Jan 4;22(1):8. doi: 10.31083/j.jin2201008.


BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) has been proven to be associated with an increased risk of cognitive impairment and dementia, and this association is more significant in non-obese NAFLD populations, but its pathogenesis remains unclear. Our study aimed to explore the abnormalities of spontaneous brain activity in non-obese NAFLD patients by resting-state fMRI (RS-fMRI) and their relationship with cognitive function.

METHODS: 19 non-obese NAFLD, 25 obese NAFLD patients, and 20 healthy controls (HC) were enrolled. All subjects underwent RS-fMRI scan, psychological scale assessment, and biochemical examination. After RS-fMRI data were preprocessed, differences in low-frequency fluctuation amplitude (ALFF), regional homogeneity (ReHo) and functional connectivity (FC) were compared among the three groups. Furthermore, the relationship between RS-fMRI indicators and cognitive and clinical indicators were performed using correlation analysis.

RESULTS: The cognitive function was declined in both NAFLD groups. Compared with obese NAFLD patients, non-obese NAFLD patients showed increased ALFF and ReHo in the left middle temporal gyrus (MTG), increased ReHo in the sensorimotor cortex and reduced FC between left MTG and right inferior frontal gyrus (IFG). Compared with HC, non-obese NAFLD patients showed increased ALFF and ReHo in the left calcarine cortex and fusiform gyrus (FG), decreased ALFF in the bilateral cerebellum, and reduced FC between left FG and right IFG and left angular gyrus. In addition to the same results, obese patients showed increased activity in different regions of the bilateral cerebellum, while decreased ALFF in the right superior frontal gyrus and ReHo in the right orbitofrontal cortex (OFC). Correlation analysis showed that in non-obese patients, the ALFF values in the FG and the FC values between the left MTG and the right IFG were associated with cognitive decline, insulin resistance, and fasting glucose disorder.

CONCLUSIONS: Non-obese NAFLD patients showed abnormal local spontaneous activity and FC in regions involved in the sensorimotor, temporo-occipital cortex, cerebellum, and reward system (such as OFC), some of which may be the potential neural mechanism difference from obese NAFLD patients. In addition, the temporo-occipital cortex may be a vulnerable target for cognitive decline in non-obese NAFLD patients.

PMID:36722230 | DOI:10.31083/j.jin2201008

Effects of the Left M1 iTBS on Brain Semantic Network Plasticity in Patients with Post-Stroke Aphasia: A Preliminary Study

Wed, 02/01/2023 - 19:00

J Integr Neurosci. 2023 Jan 17;22(1):24. doi: 10.31083/j.jin2201024.


BACKGROUND: The left primary motor area (M1) stimulation has recently been revealed to promote post-stroke aphasia (PSA) recovery, of which a plausible mechanism might be the semantic and/or the mirror neuron system reorganization, but the direct evidence is still scarce. The aim of this study was to explore the functional connectivity (FC) alterations induced by the left M1 intermittent theta burst stimulation (iTBS), a new transcranial magnetic stimulation paradigm, in the semantic and mirror neuron systems of PSA patients.

METHODS: Sixteen PSA patients accepted the left M1 iTBS and underwent a resting-state functional magnetic resonance image (fMRI) scanning before and immediately after the first session of iTBS, of which six underwent another fMRI scanning after twenty sessions of iTBS. Three brain networks covering the semantic and the mirror neuron systems were constructed using the fMRI data, and the FC alterations following one-session iTBS were investigated in the networks. Additional seed-based FC analyses were conducted to explore the longitudinal FC patterns changes during the course of multi-session iTBS. The Aphasia quotient of the Chinese version of the western aphasia battery (WAB-AQ) was used to assess the severity of the language impairments of the participants. The relationship between the longitudinal WAB-AQ and network FC changes was analyzed by Spearman's correlation coefficients in the multi-session iTBS sub-group.

RESULTS: Decreased FCs were noted in the bilateral semantic rather than in the mirror neuron networks following one-session of iTBS (p < 0.05, network based statistical corrected). Longitudinal seed-based FC analyses revealed changing FC ranges along the multi-session iTBS course, extending beyond the semantic networks. No significant relationship was found between the longitudinal WAB-AQ and network FC changes in the multi-session iTBS sub-group.

CONCLUSIONS: The left M1 iTBS might induce FC changes in the semantic system of PSA patients.

CLINICAL TRIAL REGISTRATION: This research was registered on the Chinese Clinical Trial Registry website (, and the registration number is ChiCTR2100041936.

PMID:36722227 | DOI:10.31083/j.jin2201024

Gender differences in dynamic functional network connectivity in pediatric and adult patients with attention deficit hyperactivity disorder

Tue, 01/31/2023 - 19:00

Brain Connect. 2023 Jan 31. doi: 10.1089/brain.2022.0069. Online ahead of print.


ADHD persistence into adulthood depends on gender, with 60% female and 35% male cases. This study sought to investigate gender differences in dynamic functional network connectivity (dFNC) using resting-state functional magnetic resonance imaging (rs-fMRI) data of pediatric ADHD patients (female: N=24; 11.02 ± 2.60 years, male: N=20;11.87 ± 2.62 years) and adult ADHD patients (female=19; 31.11 ± 10.40 years, males: N=20;32.05 ± 10.10 years). We identified nine and eight networks in pediatrics and adult data, respectively, using GICA. Each age group was clustered into four states using K-means. Significant gender differences in the pediatric group were only found in temporal profiles, particularly in "fraction of time" (FOT) and "mean dwell time" (MDT), but not in FNC. FOT spent by the female pediatric group in state 4 showed a negative relationship with hyperactivity severity. Compared to the adult male group, reduced connectivity was observed within the visual network, between the visual network and DMN, and FPN, as well as between the DMN and cerebellum networks in female adult ADHD patients. Significant FOT and MDT differences were observed between the two groups in state 3. Our results imply gender differences in ADHD, especially in the adult group. Furthermore, given the gender differences observed, our work provides insights into the pathophysiology of ADHD sub-served by gender.

PMID:36719777 | DOI:10.1089/brain.2022.0069

Sex based structural and functional MRI outcomes in the rat brain after soman (GD) exposure induced status epilepticus

Tue, 01/31/2023 - 19:00

Epilepsia Open. 2023 Jan 31. doi: 10.1002/epi4.12701. Online ahead of print.


OBJECTIVE: Exposure to the nerve agent, soman (GD), induces status epilepticus (SE), epileptogenesis and even death. Although rodent models studying the pathophysiological mechanisms show females to be more reactive to soman, no tangible sex differences in brains post-exposure have been reported. In this study, we used multimodal imaging using MRI in adult rats to determine potential sex-based biomarkers of soman effects.

METHODS: Male and female Sprague Dawley rats were challenged with 1.2xLD50 soman followed by medical countermeasures. Ten weeks later the brains were analyzed via structural and functional MRI.

RESULTS: Despite no significant sex differences in the initial SE severity after soman exposure, long-term MRI-based structural and functional differences were evident in the brains of both sexes. While T2 MRI showed lesser soman-induced neurodegeneration, large areas of T1 enhancements occurred in females than males, indicating a distinct pathophysiology unrelated to neurodegeneration. fMRI-based resting-state functional connectivity (RSFC), indicated greater reductions in soman-exposed females than males, associating with the T1 enhancements (unrelated to neurodegeneration) rather than T2-hyperintensity or T1-hypointensity (representing neurodegeneration). The wider T1 enhancements associating with the decreased spontaneous neuronal activity in multiple resting state networks in soman-exposed females than males suggest that neural changes unrelated to cellular atrophy impinge on brain function post-exposure. Taken together with lower spontaneous neural activity in soman exposed females, the results indicate some form of neuroprotective state that was not present in males.

SIGNIFICANCE: The results indicate that endpoints other than neurodegeneration may need to be considered to translate sex-based nerve agent effects in humans.

PMID:36718979 | DOI:10.1002/epi4.12701

Functional connectivity changes between amygdala and prefrontal cortex after ECT are associated with improvement in distinct depressive symptoms

Mon, 01/30/2023 - 19:00

Eur Arch Psychiatry Clin Neurosci. 2023 Jan 30. doi: 10.1007/s00406-023-01552-7. Online ahead of print.


Electroconvulsive therapy (ECT) is one of the most effective treatments for treatment-resistant depression. However, the underlying mechanisms of action are not yet fully understood. The investigation of depression-specific networks using resting-state fMRI and the relation to differential symptom improvement might be an innovative approach providing new insights into the underlying processes. In this naturalistic study, we investigated the relationship between changes in resting-state functional connectivity (rsFC) and symptom improvement after ECT in 21 patients with treatment-resistant depression. We investigated rsFC before and after ECT and focused our analyses on FC changes directly related to symptom reduction and on FC at baseline to identify neural targets that might predict individual clinical responses to ECT. Additional analyses were performed to identify the direct relationship between rsFC change and symptom dimensions such as sadness, negative thoughts, detachment, and neurovegetative symptoms. An increase in rsFC between the left amygdala and left dorsolateral prefrontal cortex (DLPFC) after ECT was related to overall symptom reduction (Bonferroni-corrected p = 0.033) as well as to a reduction in specific symptoms such as sadness (r = 0.524, uncorrected p = 0.014), negative thoughts (r = 0.700, Bonferroni-corrected p = 0.002) and detachment (r = 0.663, p = 0.004), but not in neurovegetative symptoms. Furthermore, high baseline rsFC between the left amygdala and the right frontal pole (FP) predicted treatment outcome (uncorrected p = 0.039). We conclude that changes in FC in regions of the limbic-prefrontal network are associated with symptom improvement, particularly in affective and cognitive dimensions. Frontal-limbic connectivity has the potential to predict symptom improvement after ECT. Further research combining functional imaging biomarkers and a symptom-based approach might be promising.

PMID:36715751 | DOI:10.1007/s00406-023-01552-7

Altered brain activity and functional connectivity after MDMA-assisted therapy for post-traumatic stress disorder

Mon, 01/30/2023 - 19:00

Front Psychiatry. 2023 Jan 12;13:947622. doi: 10.3389/fpsyt.2022.947622. eCollection 2022.


INTRODUCTION: 3,4-methylenedioxymethamphetamine-assisted therapy (MDMA-AT) for post-traumatic stress disorder (PTSD) has demonstrated promise in multiple clinical trials. MDMA is hypothesized to facilitate the therapeutic process, in part, by decreasing fear response during fear memory processing while increasing extinction learning. The acute administration of MDMA in healthy controls modifies recruitment of brain regions involved in the hyperactive fear response in PTSD such as the amygdala, hippocampus, and insula. However, to date there have been no neuroimaging studies aimed at directly elucidating the neural impact of MDMA-AT in PTSD patients.

METHODS: We analyzed brain activity and connectivity via functional MRI during both rest and autobiographical memory (trauma and neutral) response before and two-months after MDMA-AT in nine veterans and first-responders with chronic PTSD of 6 months or more.

RESULTS: We hypothesized that MDMA-AT would increase amygdala-hippocampus resting-state functional connectivity, however we only found evidence of a trend in the left amygdala-left hippocampus (t = -2.91, uncorrected p = 0.0225, corrected p = 0.0901). We also found reduced activation contrast (trauma > neutral) after MDMA-AT in the cuneus. Finally, the amount of recovery from PTSD after MDMA-AT correlated with changes in four functional connections during autobiographical memory recall: the left amygdala-left posterior cingulate cortex (PCC), left amygdala-right PCC, left amygdala-left insula, and left isthmus cingulate-left posterior hippocampus.

DISCUSSION: Amygdala-insular functional connectivity is reliably implicated in PTSD and anxiety, and both regions are impacted by MDMA administration. These findings compliment previous research indicating that amygdala, hippocampus, and insula functional connectivity is a potential target of MDMA-AT, and highlights other regions of interest related to memory processes. More research is necessary to determine if these findings are specific to MDMA-AT compared to other types of treatment for PTSD.


PMID:36713926 | PMC:PMC9879604 | DOI:10.3389/fpsyt.2022.947622

A method for reconstruction of interpretable brain networks from transient synchronization in resting-state BOLD fluctuations

Mon, 01/30/2023 - 19:00

Front Neuroinform. 2023 Jan 12;16:960607. doi: 10.3389/fninf.2022.960607. eCollection 2022.


Resting-state (rs) fMRI has been widely used to examine brain-wide large-scale spatiotemporal architectures, known as resting-state networks (RSNs). Recent studies have focused on the temporally evolving characteristics of RSNs, but it is unclear what temporal characteristics are reflected in the networks. To address this issue, we devised a novel method for voxel-based visualization of spatiotemporal characteristics of rs-fMRI with a time scale of tens of seconds. We first extracted clusters of dominant activity-patterns using a region-of-interest approach and then used these temporal patterns of the clusters to obtain voxel-based activation patterns related to the clusters. We found that activation patterns related to the clusters temporally evolved with a characteristic temporal structure and showed mutual temporal alternations over minutes. The voxel-based representation allowed the decoding of activation patterns of the clusters in rs-fMRI using a meta-analysis of functional activations. The activation patterns of the clusters were correlated with behavioral measures. Taken together, our analysis highlights a novel approach to examine brain activity dynamics during rest.

PMID:36713290 | PMC:PMC9878402 | DOI:10.3389/fninf.2022.960607

Resting state network mapping in individuals using deep learning

Mon, 01/30/2023 - 19:00

Front Neurol. 2023 Jan 12;13:1055437. doi: 10.3389/fneur.2022.1055437. eCollection 2022.


INTRODUCTION: Resting state functional MRI (RS-fMRI) is currently used in numerous clinical and research settings. The localization of resting state networks (RSNs) has been utilized in applications ranging from group analysis of neurodegenerative diseases to individual network mapping for pre-surgical planning of tumor resections. Reproducibility of these results has been shown to require a substantial amount of high-quality data, which is not often available in clinical or research settings.

METHODS: In this work, we report voxelwise mapping of a standard set of RSNs using a novel deep 3D convolutional neural network (3DCNN). The 3DCNN was trained on publicly available functional MRI data acquired in n = 2010 healthy participants. After training, maps that represent the probability of a voxel belonging to a particular RSN were generated for each participant, and then used to calculate mean and standard deviation (STD) probability maps, which are made publicly available. Further, we compared our results to previously published resting state and task-based functional mappings.

RESULTS: Our results indicate this method can be applied in individual subjects and is highly resistant to both noisy data and fewer RS-fMRI time points than are typically acquired. Further, our results show core regions within each network that exhibit high average probability and low STD.

DISCUSSION: The 3DCNN algorithm can generate individual RSN localization maps, which are necessary for clinical applications. The similarity between 3DCNN mapping results and task-based fMRI responses supports the association of specific functional tasks with RSNs.

PMID:36712434 | PMC:PMC9878609 | DOI:10.3389/fneur.2022.1055437

Preoperative functional connectivity by magnetic resonance imaging for refractory neocortical epilepsy

Mon, 01/30/2023 - 19:00

medRxiv. 2023 Jan 11:2023.01.10.23284374. doi: 10.1101/2023.01.10.23284374. Preprint.


OBJECTIVE: Patients with refractory epilepsy experience extensive and invasive clinical testing for seizure onset zones treatable by surgical resection. However, surgical resection can fail to provide therapeutic benefit, and patients with neocortical epilepsy have the poorest therapeutic outcomes. This case series studied patients with neocortical epilepsy who were referred for surgical treatment. Prior to surgery, patients volunteered for resting-state functional magnetic resonance imaging (rs-fMRI) in addition to imaging for the clinical standard of care. This work examined the variability of functional connectivity in patients, estimated from rs-fMRI, for associations with surgical outcomes.

METHODS: This work examined pre-operative structural imaging, pre-operative rs-fMRI, and post-operative structural imaging from seven epilepsy patients. Review of the clinical record provided Engel classifications for surgical outcomes. A novel method assessed pre-operative rs-fMRI from patients using comparative rs-fMRI from a large cohort of healthy control subjects and estimated Gibbs distributions for functional connectivity in patients compared to healthy controls.

RESULTS: Three patients had Engel classification Ia, one patient had Engel classification IIa, and three patients had Engel classification IV. Metrics for variability of functional connectivity, including absolute differences of the functional connectivity of each patient from healthy control averages and probabilistic scores for absolute differences, were higher for patients classified as Engel IV, for whom epilepsy surgery provided no meaningful improvement.

SIGNIFICANCE: This work continues on-going efforts to use rs-fMRI to characterize abnormal functional connectivity in the brain. Preliminary evidence indicates that the topography of variant functional connectivity in epilepsy patients may be clinically relevant for identifying patients unlikely to have favorable outcomes after epilepsy surgery. Widespread topographic variations of functional connectivity also support the hypothesis that epilepsy is a disease of brain resting-state networks.

PMID:36712003 | PMC:PMC9882436 | DOI:10.1101/2023.01.10.23284374