Corrigendum: Neurophysiological hallmarks of Huntington's disease progression: an EEG and fMRI connectivity study.

[This corrects the article DOI: 10.3389/fnagi.2023.1270226.].

The mesolimbic system and the loss of higher order network features in schizophrenia when learning without reward.

Introduction: Schizophrenia is characterized by a loss of network features between cognition and reward sub-circuits (notably involving the mesolimbic system), and this loss may explain deficits in learning and cognition. Learning in schizophrenia has typically been studied with tasks that include reward related contingencies, but recent theoretical models have argued that a loss of network features should be seen even when learning without reward. We tested this model using a learning paradigm that required participants to learn without reward or feedback. We used a novel method for capturing higher order network features, to demonstrate that the mesolimbic system is heavily implicated in the loss of network features in schizophrenia, even when learning without reward. Methods: fMRI data (Siemens Verio 3T) were acquired in a group of schizophrenia patients and controls (n=78; 46 SCZ, 18 ≤ Age ≤ 50) while participants engaged in associative learning without reward-related contingencies. The task was divided into task-active conditions for encoding (of associations) and cued-retrieval (where the cue was to be used to retrieve the associated memoranda). No feedback was provided during retrieval. From the fMRI time series data, network features were defined as follows: First, for each condition of the task, we estimated 2nd order undirected functional connectivity for each participant (uFC, based on zero lag correlations between all pairs of regions). These conventional 2nd order features represent the task/condition evoked synchronization of activity between pairs of brain regions. Next, in each of the patient and control groups, the statistical relationship between all possible pairs of 2nd order features were computed. These higher order features represent the consistency between all possible pairs of 2nd order features in that group and embed within them the contributions of individual regions to such group structure. Results: From the identified inter-group differences (SCZ ≠ HC) in higher order features, we quantified the respective contributions of individual brain regions. Two principal effects emerged: 1) SCZ were characterized by a massive loss of higher order features during multiple task conditions (encoding and retrieval of associations). 2) Nodes in the mesolimbic system were over-represented in the loss of higher order features in SCZ, and notably so during retrieval. Discussion: Our analytical goals were linked to a recent circuit-based integrative model which argued that synergy between learning and reward circuits is lost in schizophrenia. The model's notable prediction was that such a loss would be observed even when patients learned without reward. Our results provide substantial support for these predictions where we observed a loss of network features between the brain's sub-circuits for a) learning (including the hippocampus and prefrontal cortex) and b) reward processing (specifically constituents of the mesolimbic system that included the ventral tegmental area and the nucleus accumbens. Our findings motivate a renewed appraisal of the relationship between reward and cognition in schizophrenia and we discuss their relevance for putative behavioral interventions.

Repetitive Transcranial Magnetic Stimulation (rTMS) Treatment Reduces Variability in Brain Function in Schizophrenia: Data From a Double-Blind, Randomized, Sham-Controlled Trial.

BACKGROUND/HYPOTHESIS: There is increasing awareness of interindividual variability in brain function, with potentially major implications for repetitive transcranial magnetic stimulation (rTMS) efficacy. We perform a secondary analysis using data from a double-blind randomized controlled 4-week trial of 20 Hz active versus sham rTMS to dorsolateral prefrontal cortex (DLPFC) during a working memory task in participants with schizophrenia. We hypothesized that rTMS would change local functional activity and variability in the active group compared with sham. STUDY DESIGN: 83 participants were randomized in the original trial, and offered neuroimaging pre- and post-treatment. Of those who successfully completed both scans (n = 57), rigorous quality control left n = 42 (active/sham: n = 19/23), who were included in this analysis. Working memory-evoked activity during an N-Back (3-Back vs 1-Back) task was contrasted. Changes in local brain activity were examined from an 8 mm ROI around the rTMS coordinates. Individual variability was examined as the mean correlational distance (MCD) in brain activity pattern from each participant to others within the same group. RESULTS: We observed an increase in task-evoked left DLPFC activity in the active group compared with sham (F1,36 = 5.83, False Discovery Rate (FDR))-corrected P = .04). Although whole-brain activation patterns were similar in both groups, active rTMS reduced the MCD in activation pattern compared with sham (F1,36 = 32.57, P < .0001). Reduction in MCD was associated with improvements in attention performance (F1,16 = 14.82, P = .0014, uncorrected). CONCLUSIONS: Active rTMS to DLPFC reduces individual variability of brain function in people with schizophrenia. Given that individual variability is typically higher in schizophrenia patients compared with controls, such reduction may "normalize" brain function during higher-order cognitive processing.

Examining the relationship between psychosocial adversity and inhibitory control: A functional magnetic resonance imaging study of children growing up in extreme poverty.

Exposure to psychosocial adversity (PA) is associated with poor behavioral, physical, and mental health outcomes in adulthood. As these outcomes are related to alterations in developmental processes, growing evidence suggests that deficits in executive functions-inhibitory control in particular-may in part explain this relationship. However, literature examining the development of inhibitory control has been based on children in higher-resource environments, and little is known how low-resource settings might exacerbate the link between inhibitory control and health outcomes. In this context, we collected functional magnetic resonance imaging data during a Go/No-Go inhibitory control task and PA variables for 68 children aged 5 to 7 years living in Dhaka, Bangladesh, an area with a high prevalence of PA. The children's mothers completed behavioral questionnaires to assess the children's PA and their own PA. Whole-brain activation underlying inhibitory control was examined using the No-Go versus Go contrast, and associations with PA variables were assessed using whole-brain regressions. Childhood neglect was associated with weaker activation in the right posterior cingulate, whereas greater family conflict, economic stress, and maternal PA factors were associated with greater activation in the left medial frontal gyrus, right superior and middle frontal gyri, and left cingulate gyrus. These data suggest that neural networks supporting inhibitory control processes may vary as a function of exposure to different types of PA, particularly between those related to threat and deprivation. Furthermore, increased activation in children with greater PA may serve as a compensatory mechanism, allowing them to maintain similar behavioral task performance.

Cerebrovascular Reactivity Assessed by Breath-Hold Functional MRI in Patients with Neurological Post-COVID-19 Syndrome-A Pilot Study.

Endothelial dysfunction represents a potential pathomechanism of neurological post-COVID-19 syndrome (PCS). A recent study demonstrated reduced cerebrovascular reactivity (CVR) in patients with PCS. The aim of this pilot study was to prospectively assess CVR in patients with PCS using breath-hold functional MRI (bh-fMRI). Fourteen patients with neurological PCS and leading symptoms of fatigue/memory issues/concentration disorder (PCSfmc), 11 patients with PCS and leading symptoms of myopathy/neuropathy (PCSmn), and 17 healthy controls underwent bh-fMRI. Signal change and time to peak (TTP) were assessed globally and in seven regions of interest and compared between the subgroups using one-way ANCOVA adjusting for age, time since infection, Fazekas score, and sex. No significant differences were observed. In PCS patients, the global CVR exhibited a slight, non-significant tendency to be lower compared to healthy controls (PCSfmc: 0.78 ± 0.11%, PCSmn: 0.84 ± 0.10% and 0.87 ± 0.07%). There was a non-significant trend towards lower global TTP values in the PCS subgroups than in the control group (PCSfmc: 26.41 ± 1.39 s, PCSmn: 26.32 ± 1.36 s versus 29.52 ± 0.93 s). Endothelial dysfunction does not seem to be the sole pathomechanism of neurological symptoms in PCS. Further studies in larger cohorts are required.

Predicting Task Activation Maps from Resting-State Functional Connectivity using Deep Learning.

Recent work has shown that deep learning is a powerful tool for predicting brain activation patterns evoked through various tasks using resting state features. We replicate and improve upon this recent work to introduce two models, BrainSERF and BrainSurfGCN, that perform at least as well as the state-of-the-art while greatly reducing memory and computational footprints. Our performance analysis observed that low predictability was associated with a possible lack of task engagement derived from behavioral performance. Furthermore, a deficiency in model performance was also observed for closely matched task contrasts, likely due to high individual variability confirmed by low test-retest reliability. Overall, we successfully replicate recently developed deep learning architecture and provide scalable models for further research.

The Contribution of Cognitive Control Networks in Word Selection Processing in Parkinson's Disease: Novel Insights from a Functional Connectivity Study.

Parkinson's disease (PD) patients are impaired in word production when the word has to be selected among competing alternatives requiring higher attentional resources. In PD, word selection processes are correlated with the structural integrity of the inferior frontal gyrus, which is critical for response selection, and the uncinate fasciculus, which is necessary for processing lexical information. In early PD, we investigated the role of the main cognitive large-scale networks, namely the salience network (SN), the central executive networks (CENs), and the default mode network (DMN), in word selection. Eighteen PD patients and sixteen healthy controls were required to derive nouns from verbs or generate verbs from nouns. Participants also underwent a resting-state functional MRI. Functional connectivity (FC) was examined using independent component analysis. Functional seeds for the SN, CENs, and DMN were defined as spheres, centered at the local activation maximum. Correlations were calculated between the FC of each functional seed and word production. A significant association between SN connectivity and task performance and, with less evidence, between CEN connectivity and the task requiring selection among a larger number of competitors, emerged in the PD group. These findings suggest the involvement of the SN and CEN in word selection in early PD, supporting the hypothesis of impaired executive control.

Two sides of the same coin? What neural processing of emotion and rewards can tell us about complex post-traumatic stress disorder and borderline personality disorder.

BACKGROUND: Borderline personality disorder (BPD) and complex posttraumatic stress disorder (cPTSD) share clinical similarities, complicating diagnosis and treatment. Research on the neurobiology of BPD and monotraumatic PTSD has shown that a prefrontal-limbic imbalance in emotional and reward processing is a hallmark of both disorders, but studies examining this network in cPTSD are lacking. Therefore, this study aimed to directly compare neural processing of emotion and reward during decision making in cPTSD and BPD. METHODS: Using functional magnetic resonance imaging, we measured neural activity in female patients (27 patients with cPTSD, 21 patients with BPD and 37 healthy controls) during a Desire-Reason Dilemma task featuring distracting fearful facial expressions. RESULTS: We found no differences in neural activation when comparing cPTSD and BPD. However, when grouping patients based on symptom severity instead on diagnosis, we found that increased symptoms of cPTSD were associated with increased activation of dorsolateral prefrontal cortex during reward rejection, whereas increased symptoms of BPD were associated with decreased activation in prefrontal and limbic regions during reward rejection with distracting negative emotional stimuli. CONCLUSION: This is the first study to investigate and compare emotional processing and reward-based decision making in cPTSD and BPD. Although we found no neural differences between disorders, we identified symptom-related neural patterns. Specifically, we found that elevated cPTSD symptoms were related to greater sensitivity to reward stimuli, whereas heightened BPD symptoms were related to increased susceptibility to emotional stimuli during goal-directed decision making. These findings enhance our understanding of neural pathomechanisms in trauma-related disorders.

Rest-fMRI-A Potential Substitute for Task-fMRI?

Objective The aim of this study was to assess the reliability of resting-state functional magnetic resonance imaging (rest-fMRI) in mapping language areas for preoperative planning, versus standard task-based techniques, which are at times difficult to perform in clinical settings. Our study also aimed to evaluate the overlap between language areas identified through rest-fMRI and the standard task-fMRI, in neurosurgical cases. Materials and Methods Using a seed-based analysis of rest-fMRI with multiple template seeds, we identified functionally connected language regions in patients undergoing preoperative language mapping. Four language task paradigms (word, verb, picture, and semantics) were evaluated. We quantified the degree of overlap between language areas identified on rest-fMRI and task-fMRI, categorizing the results as more than 50% or less than 50% overlap. Results Seventy-seven percent of patients demonstrated an overlap exceeding 50% between rest- and task-fMRI maps, with the left Broca's area being the most frequently observed region of overlap. This finding was noted even in cases with lesions in Broca's or Wernicke's areas, highlighting the method's robustness. The verb task showed the best blood-oxygen-level dependent activity and overlap with rest-fMRI, highlighting its reliability. To identify a specific language area, the contralateral seed of the same area most commonly displayed connectivity with the area of interest. Conclusion Our findings demonstrate the potential of using rest-fMRI in accurately mapping eloquent language areas, in clinical settings The strong concordance observed, especially in the left Broca's area, underscores the reliability of this method. Further research and larger studies are essential to validate these results, potentially establishing the use of routine rest-fMRI, in clinical preoperative workup.

Functional MRI study with conductivity signal changes during visual stimulation.

BACKGROUND: Although blood oxygen level-dependent (BOLD) functional MRI (fMRI) is a standard method, major BOLD signals primarily originate from intravascular sources. Magnetic resonance electrical properties tomography (MREPT)-based fMRI signals may provide additional insights into electrical activity caused by alterations in ion concentrations and mobilities. PURPOSE: This study aimed to investigate the neuronal response of conductivity during visual stimulation and compare it with BOLD. MATERIALS AND METHODS: A total of 30 young, healthy volunteers participated in two independent experiments using BOLD and MREPT techniques with a visual stimulation paradigm at 3 T MRI. The first set of MREPT fMRI data was obtained using a multi-echo spin-echo (SE) echo planar imaging (EPI) sequence from 14 participants. The second set of MREPT fMRI data was collected from 16 participants using both a single-echo SE-EPI and a single-echo three-dimensional (3D) balanced fast-field-echo (bFFE) sequence. We reconstructed the time-course Larmor frequency conductivity to evaluate hemodynamics. RESULTS: Conductivity values slightly increased during visual stimulation. Activation strengths were consistently stronger with BOLD than with conductivity for both SE-EPI MREPT and bFFE MREPT. Additionally, the activated areas were always larger with BOLD than MREPT. Some participants also exhibited decreased conductivity values during visual stimulations. In Experiment 1, conductivity showed significant differences between the fixation and visual stimulation blocks in the secondary visual cortex (SVC) and cuneus, with conductivity differences of 0.43 % and 0.47 %, respectively. No significant differences in conductivity were found in the cerebrospinal fluid (CSF) areas between the two blocks. In Experiment 2, significant conductivity differences were observed between the two blocks in the SVC, cuneus, and lingual gyrus for SE-EPI MREPT, with differences of 0.90 %, 0.67 %, and 0.24 %, respectively. Again, no significant differences were found in the CSF areas. CONCLUSION: Conductivity values increased slightly during visual stimulation in the visual cortex areas but were much weaker than BOLD responses. The conductivity change during visual stimulation was less than 1 % compared to the fixation block. No significant differences in conductivity were observed between the primary visual cortex (PVC)-CSF and SVC-CSF during fixation and visual stimulations, suggesting that the observed conductivity changes may not be related to CSF changes in the visual cortex but rather to diffusion changes. Future research should explore the potential of MREPT to detect neuronal electrical activity and hemodynamic changes, with further optimization of the MREPT technique.

Classifying Unconscious, Psychedelic, and Neuropsychiatric Brain States with Functional Connectivity, Graph Theory, and Cortical Gradient Analysis.

Accurate and generalizable classification of brain states is essential for understanding their neural underpinnings and improving clinical diagnostics. Traditionally, functional connectivity patterns and graph-theoretic metrics have been utilized. However, cortical gradient features, which reflect global brain organization, offer a complementary approach. We hypothesized that a machine learning model integrating these three feature sets would effectively discriminate between baseline and atypical brain states across a wide spectrum of conditions, even though the underlying neural mechanisms vary. To test this, we extracted features from brain states associated with three meta-conditions including unconsciousness (NREM2 sleep, propofol deep sedation, and propofol general anesthesia), psychedelic states induced by hallucinogens (subanesthetic ketamine, lysergic acid diethylamide, and nitrous oxide), and neuropsychiatric disorders (attention-deficit hyperactivity disorder, bipolar disorder, and schizophrenia). We used support vector machine with nested cross-validation to construct our models. The soft voting ensemble model marked the average balanced accuracy (average of specificity and sensitivity) of 79% (62-98% across all conditions), outperforming individual base models (70-76%). Notably, our models exhibited varying degrees of transferability across different datasets, with performance being dependent on the specific brain states and feature sets used. Feature importance analysis across meta-conditions suggests that the underlying neural mechanisms vary significantly, necessitating tailored approaches for accurate classification of specific brain states. This finding underscores the value of our feature-integrated ensemble models, which leverage the strengths of multiple feature types to achieve robust performance across a broader range of brain states. While our approach offers valuable insights into the neural signatures of different brain states, future work is needed to develop and validate even more generalizable models that can accurately classify brain states across a wider array of conditions.

The application value of Rs-fMRI-based machine learning models for differentiating mild cognitive impairment from Alzheimer's disease: a systematic review and meta-analysis.

BACKGROUND: Various machine learning (ML) models based on resting-state functional MRI (Rs-fMRI) have been developed to facilitate differential diagnosis of mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, the diagnostic accuracy of such models remains understudied. Therefore, we conducted this systematic review and meta-analysis to explore the diagnostic accuracy of Rs-fMRI-based radiomics in differentiating MCI from AD. METHODS: PubMed, Embase, Cochrane, and Web of Science were searched from inception up to February 8, 2024, to identify relevant studies. Meta-analysis was conducted using a bivariate mixed-effects model, and sub-group analyses were carried out by the types of ML tasks (binary classification and multi-class classification tasks). FINDINGS: In total, 23 studies, comprising 5,554 participants were enrolled in the study. In the binary classification tasks (twenty studies), the diagnostic accuracy of the ML model for AD was 0.99 (95%CI: 0.34 ~ 1.00), with a sensitivity of 0.94 (95%CI: 0.89 ~ 0.97) and a specificity of 0.98 (95%CI: 0.95 ~ 1.00). In the multi-class classification tasks (six studies), the diagnostic accuracy of the ML model was 0.98 (95%CI: 0.98 ~ 0.99) for NC, 0.96 (95%CI: 0.96 ~ 0.96) for early mild cognitive impairment (EMCI), 0.97 (95%CI: 0.96 ~ 0.97) for late mild cognitive impairment (LMCI), and 0.95 (95%CI: 0.95 ~ 0.95) for AD. CONCLUSIONS: The Rs-fMRI-based ML model can be adapted to multi-class classification tasks. Therefore, multi-center studies with large samples are needed to develop intelligent application tools to promote the development of intelligent ML models for disease diagnosis.

Coupled pulsatile vascular and paravascular fluid dynamics in the human brain.

BACKGROUND: Cardiac pulsation propels blood through the cerebrovascular network to maintain cerebral homeostasis. The cerebrovascular network is uniquely surrounded by paravascular cerebrospinal fluid (pCSF), which plays a crucial role in waste removal, and its flow is suspected to be driven by arterial pulsations. Despite its importance, the relationship between vascular and paravascular fluid dynamics throughout the cardiac cycle remains poorly understood in humans. METHODS: In this study, we developed a non-invasive neuroimaging approach to investigate the coupling between pulsatile vascular and pCSF dynamics within the subarachnoid space of the human brain. Resting-state functional MRI (fMRI) and dynamic diffusion-weighted imaging (dynDWI) were retrospectively cardiac-aligned to represent cerebral hemodynamics and pCSF motion, respectively. We measured the time between peaks (∆TTP) in d d ϕ f M R I and dynDWI waveforms and measured their coupling by calculating the waveforms correlation after peak alignment (correlation at aligned peaks). We compared the ∆TTP and correlation at aligned peaks between younger [mean age: 27.9 (3.3) years, n = 9] and older adults [mean age: 70.5 (6.6) years, n = 20], and assessed their reproducibility within subjects and across different imaging protocols. RESULTS: Hemodynamic changes consistently precede pCSF motion. ∆TTP was significantly shorter in younger adults compared to older adults (-0.015 vs. -0.069, p < 0.05). The correlation at aligned peaks were high and did not differ between younger and older adults (0.833 vs. 0.776, p = 0.153). The ∆TTP and correlation at aligned peaks were robust across fMRI protocols (∆TTP: -0.15 vs. -0.053, p = 0.239; correlation at aligned peaks: 0.813 vs. 0.812, p = 0.985) and demonstrated good to excellent within-subject reproducibility (∆TTP: intraclass correlation coefficient = 0.36; correlation at aligned peaks: intraclass correlation coefficient = 0.89). CONCLUSION: This study proposes a non-invasive technique to evaluate vascular and paravascular fluid dynamics. Our findings reveal a consistent and robust cardiac pulsation-driven coupling between cerebral hemodynamics and pCSF dynamics in both younger and older adults.

Alteration in temporal-cerebellar effective connectivity can effectively distinguish stable and progressive mild cognitive impairment.

Background: Stable mild cognitive impairment (sMCI) and progressive mild cognitive impairment (pMCI) represent two distinct subtypes of mild cognitive impairment (MCI). Early and effective diagnosis and accurate differentiation between sMCI and pMCI are crucial for administering targeted early intervention and preventing cognitive decline. This study investigated the intrinsic dysconnectivity patterns in sMCI and pMCI based on degree centrality (DC) and effective connectivity (EC) analyses, with the goal of uncovering shared and distinct neuroimaging mechanisms between subtypes. Methods: Resting-state functional magnetic resonance imaging combined with DC analysis was used to explore the functional connectivity density in 42 patients with sMCI, 31 patients with pMCI, and 82 healthy control (HC) participants. Granger causality analysis was used to assess changes in EC based on the significant clusters found in DC. Furthermore, correlation analysis was conducted to examine the associations between altered DC/EC values and cognitive function. Receiver operating characteristic curve analysis was performed to determine the accuracy of abnormal DC and EC values in distinguishing sMCI from pMCI. Results: Compared with the HC group, both pMCI and sMCI groups exhibited increased DC in the left inferior temporal gyrus (ITG), left posterior cerebellum lobe (CPL), and right cerebellum anterior lobe (CAL), along with decreased DC in the left medial frontal gyrus. Moreover, the sMCI group displayed reduced EC from the right CAL to bilateral CPL, left superior temporal gyrus, and bilateral caudate compared with HC. pMCI demonstrated elevated EC from the right CAL to left ITG, which was linked to episodic memory and executive function. Notably, the EC from the right CAL to the right ITG effectively distinguished sMCI from pMCI, with sensitivity, specificity, and accuracy of 0.5806, 0.9512, and 0.828, respectively. Conclusion: This study uncovered shared and distinct alterations in DC and EC between sMCI and pMCI, highlighting their involvement in cognitive function. Of particular significance are the unidirectional EC disruptions from the cerebellum to the temporal lobe, which serve as a discriminating factor between sMCI and pMCI and provide a new perspective for understanding the temporal-cerebellum. These findings offer novel insights into the neural circuit mechanisms involving the temporal-cerebellum connection in MCI.

Molecular mechanisms and behavioral relevance underlying neural correlates of childhood neglect.

BACKGROUND: Childhood neglect is associated with brain changes, yet the molecular mechanisms and behavioral relevance underlying such associations remain elusive. METHODS: We calculated fractional amplitude of low-frequency fluctuations (fALFF) using resting-state functional MRI and tested their correlation with childhood neglect across a large sample of 510 healthy young adults. Then, we investigated the spatial relationships of the identified neural correlates of childhood neglect with gene expression, neurotransmitter, and behavioral domain atlases. RESULTS: We found that more severe childhood neglect was correlated with higher fALFF in the bilateral anterior cingulate cortex. Remarkably, the identified neural correlates of childhood neglect were spatially correlated with expression of gene categories primarily involving neuron, synapse, ion channel, cognitive and perceptual processes, and physiological response and regulation. Concurrently, there were significant associations between the neural correlates and specific neurotransmitter systems including serotonin and GABA. Finally, neural correlates of childhood neglect were associated with diverse behavioral domains implicating mental disorders, emotion, cognition, and sensory perception. LIMITATIONS: The cross-sectional study design cannot unequivocally establish causality. CONCLUSIONS: Our findings may not only add to the current knowledge regarding the relationship between childhood neglect and mental health, but also have clinical implications for developing preventive strategies for individuals exposed to childhood neglect who are at risk for mental disorders.

Correlation Between the Fractional Amplitude of Low-Frequency Fluctuation and Cognitive Defects in Alzheimer's Disease.

Background: The fractional amplitude of low-frequency fluctuations (fALFFs) can detect spontaneous brain activity. However, the association between abnormal brain activity and cognitive function, amyloid protein (Aß), and emotion in Alzheimer's disease (AD) patients remains unclear. Objective: This study aimed to survey alterations in fALFF in different frequency bands and the relationship between abnormal brain activity, depressive mood, and cognitive function to determine the potential mechanism of AD. Methods: We enrolled 34 AD patients and 32 healthy controls (HC). All the participants underwent resting-state magnetic resonance imaging, and slow-4 and slow-5 fALFF values were measured. Subsequently, the study determined the correlation of abnormal brain activity with mood and cognitive function scores. Results: AD patients revealed altered mfALFF values in the slow-5 and slow-4 bands. In the slow-4 band, the altered mfALFF regions were the right cerebellar crus I, right inferior frontal orbital gyrus (IFOG), right supramarginal gyrus, right precuneus, angular gyrus, and left middle cingulate gyrus. Elevated mfALFF values in the right IFOG were negatively associated with Montreal Cognitive Assessment scores, Boston Naming Test, and Aß1-42 levels. The mfALFF value of the AD group was lower than the HC group in the slow-5 band, primarily within the right inferior parietal lobule and right precuneus. Conclusions: Altered mfALFF values in AD patients are linked with cognitive dysfunction. Compared with HCs, Aß1-42 levels in AD patients are related to abnormal IFOG activity. Therefore, mfALFF could be a potential biomarker of AD.

White matter microstructure and functional connectivity in the brains of infants with Turner syndrome.

Turner syndrome, caused by complete or partial loss of an X-chromosome, is often accompanied by specific cognitive challenges. Magnetic resonance imaging studies of adults and children with Turner syndrome suggest these deficits reflect differences in anatomical and functional connectivity. However, no imaging studies have explored connectivity in infants with Turner syndrome. Consequently, it is unclear when in development connectivity differences emerge. To address this gap, we compared functional connectivity and white matter microstructure of 1-year-old infants with Turner syndrome to typically developing 1-year-old boys and girls. We examined functional connectivity between the right precentral gyrus and five regions that show reduced volume in 1-year old infants with Turner syndrome compared to controls and found no differences. However, exploratory analyses suggested infants with Turner syndrome have altered connectivity between right supramarginal gyrus and left insula and right putamen. To assess anatomical connectivity, we examined diffusivity indices along the superior longitudinal fasciculus and found no differences. However, an exploratory analysis of 46 additional white matter tracts revealed significant group differences in nine tracts. Results suggest that the first year of life is a window in which interventions might prevent connectivity differences observed at later ages, and by extension, some of the cognitive challenges associated with Turner syndrome.

Associations between perceived parenting, brain activity and connectivity, and depression symptoms in Brazilian adolescents.

In adolescence, parental care is associated with lower depression symptoms whereas parental overprotection is associated with greater depression symptoms, effects which may be mediated by adolescent brain activity and connectivity. The present study examined associations between perceived parenting, brain activity and connectivity, and depression symptoms in adolescents from Brazil, a middle-income country (MIC). Analyses included 100 adolescents who underwent functional magnetic resonance imaging scanning while completing a face matching task. Parental care and overprotection were associated with adolescent depression symptoms in expected directions. We also found that parental care and overprotection were associated with amygdala connectivity with several brain regions; however, amygdala activity was not associated with parenting and neither activity or connectivity mediated the association between parenting and depression symptoms. Results identify how parenting influences brain function and depression symptoms in youth from a MIC.

Alterations of perfusion and functional connectivity of the cingulate motor area are associated with psychomotor retardation in major depressive disorder.

Psychomotor retardation, characterized by slowing of speech, thoughts, and a decrease of movements, is frequent in patients with major depressive disorder (MDD). However, its neurobiological correlates are still poorly understood. This study aimed to explore if cerebral blood flow (CBF) and resting state functional connectivity (rs-FC) of the motor network are altered in patients with MDD and if these changes are associated with psychomotor retardation. Thirty-six right-handed patients with depression and 19 right-handed healthy controls (HC) that did not differ regarding age and sex underwent arterial spin labelling (ASL) and resting-state functional MRI (rs-fMRI) scans. Psychomotor retardation was assessed with the motoric items of the core assessment of psychomotor change (CORE) questionnaire. Patients with MDD had more pronounced psychomotor retardation scores than HC. Patients with MDD had reduced CBF in bilateral cingulate motor area (CMA) and increased resting-state functional connectivity (rs-FC) between the cluster in the CMA and a cluster localized in bilateral supplementary motor areas (SMA). Furthermore, increased rs-FC between the CMA and the left SMA was associated with more pronounced psychomotor retardation. Our results suggest that reduced perfusion of the CMA and increased rs-FC between the CMA and the SMA are associated with psychomotor retardation in patients with depression.

Monoaminergic network abnormalities are associated with fatigue in pediatric multiple sclerosis.

BACKGROUND: Fatigue is commonly observed in pediatric multiple sclerosis (pedMS) patients, but its underlying mechanisms remain largely unexplored. We evaluated whether resting-state (RS) functional connectivity (FC) abnormalities in monoaminergic networks contributed to explain fatigue in pedMS. METHODS: Fifty-five pedMS and twenty-three matched healthy controls (HC) underwent clinical and RS functional MRI assessment. Patients with Fatigue Severity Scale (FSS) score ≥ 4 were classified as fatigued (F). Patterns of dopamine-, noradrenaline- and serotonin-related RS FC were derived by constrained independent component analysis, using PET atlases for dopamine, noradrenaline, and serotonin transporters obtained in HCs' brain. RESULTS: Compared to non-fatigued (NF)-pedMS patients and HC, F-pedMS patients (15/55, 27.3%) showed decreased dopamine-related RS FC in the right postcentral gyrus. They also showed decreased dopamine-related RS FC in the left insula vs. HC and increased dopamine-related RS FC in the left middle temporal gyrus and cerebellum (lobule VI) vs. NF patients. In the noradrenaline-related network, F-pedMS patients showed decreased RS FC in the left superior parietal lobule and increased RS FC in the right thalamus vs. HC and NF-pedMS. Compared to HC, F-pedMS patients also showed decreased RS FC in the right calcarine cortex and increased RS FC in the right middle frontal gyrus. In the serotonin-related network, F-pedMS patients showed decreased RS FC in the right angular gyrus and increased RS FC in the right postcentral gyrus vs. NF-pedMS patients. DISCUSSION: In pedMS, fatigue is associated with specific monoaminergic network abnormalities, providing pathological markers for this bothersome symptom and putative targets for its treatment.