State fMRI Research Articles

Identifying the Neural Correlates of Resting State Affect Processing Dynamics.

There exists growing interest in understanding the dynamics of resting state functional magnetic resonance imaging (rs-fMRI) to establish mechanistic links between individual patterns of spontaneous neural activation and corresponding behavioral measures in both normative and clinical populations. Here we propose and validate a novel approach in which whole-brain rs-fMRI data are mapped to a specific low-dimensional representation-affective valence and arousal processing-prior to dynamic analysis. This mapping process constrains the state space such that both independent validation and visualization of the system's dynamics become tractable. To test this approach, we constructed neural decoding models of affective valence and arousal processing from brain states induced by International Affective Picture Set image stimuli during task-related fMRI in (n = 97) healthy control subjects. We applied these models to decode moment-to-moment affect processing in out-of-sample subjects' rs-fMRI data and computed first and second temporal derivatives of the resultant valence and arousal time-series. Finally, we fit a second set of neural decoding models to these derivatives, which function as neurally constrained ordinary differential equations (ODE) underlying affect processing dynamics. To validate these decodings, we simulated affect processing by numerical integration of the true temporal sequence of neurally decoded derivatives for each subject and demonstrated that these decodings generate significantly less (p < 0.05) group-level simulation error than integration based upon decoded derivatives sampled uniformly randomly from the true temporal sequence. Indeed, simulations of valence and arousal processing were significant for up to four steps of closed-loop simulation (Δt = 2.0 s) for both valence and arousal, respectively. Moreover, neural encoding representations of the ODE decodings include significant clusters of activation within brain regions associated with affective reactivity and regulation. Our work has methodological implications for efforts to identify unique and actionable biomarkers of possible future or current psychopathology, particularly those related to mood and emotional instability.

Resting State Functional Connectivity between Dorsal Attentional Network and Right Inferior Frontal Gyrus in Concussed and Control Adolescents.

Concussion among adolescents continues to be a public health concern. Yet, the differences in brain function between adolescents with a recent concussion and adolescents with no history of concussion are not well understood. Although resting state functional magnetic resonance imaging (fMRI) can be a useful tool in examining these differences, few studies have used this technique to examine concussion in adolescents. Here, we investigate the differences in the resting state functional connectivity of 52 adolescents, 38 with a concussion in the previous 10 days (mean age = 15.6; female = 36.8%), and 14 controls with no concussion history (mean age = 15.1; female = 57.1%). Independent component analysis and dual regression revealed that control adolescents had significantly greater functional connectivity between the dorsal attention network (DAN) and right inferior frontal gyrus (RIFG) compared to concussed adolescents (p-corrected < 0.001). Specifically, there was a positive DAN-RIFG connectivity in control, but not concussed, adolescents. Our findings indicate that concussion is associated with disrupted DAN-RIFG connectivity, which may reflect a general, nonspecific response to injury.

Multiframe Evolving Dynamic Functional Connectivity (EVOdFNC): A Method for Constructing and Investigating Functional Brain Motifs.

The study of brain network connectivity as a time-varying property began relatively recently and, to date, has remained primarily concerned with capturing a handful of discrete static states that characterize connectivity as measured on a timescale shorter than that of the full scan. Capturing group-level representations of temporally evolving patterns of connectivity is a challenging and important next step in fully leveraging the information available in large resting state functional magnetic resonance imaging (rs-fMRI) studies. We introduce a flexible, extensible data-driven framework for the stable identification of group-level multiframe (movie-style) dynamic functional network connectivity (dFNC) states. Our approach employs uniform manifold approximation and embedding (UMAP) to produce a continuity-preserving planar embedding of high-dimensional time-varying measurements of whole-brain functional network connectivity. Planar linear exemplars summarizing dominant dynamic trends across the population are computed from local linear approximations to the two-dimensional 2D embedded trajectories. A high-dimensional representation of each 2D exemplar segment is obtained by averaging the dFNC observations corresponding to the n planar nearest neighbors of τ evenly spaced points along the 2D line segment representation (where n is the UMAP number-of-neighbors parameter and τ is the temporal duration of trajectory segments being approximated). Each of the 2D exemplars thus “lifts” to a multiframe high-dimensional dFNC trajectory of length τ. The collection of high-dimensional temporally evolving dFNC representations (EVOdFNCs) derived in this manner are employed as dynamic basis objects with which to characterize observed high-dimensional dFNC trajectories, which are then expressed as weighted combination of these basis objects. Our approach yields new insights into anomalous patterns of fluidly varying whole-brain connectivity that are significantly associated with schizophrenia as a broad diagnosis as well as with certain symptoms of this serious disorder. Importantly, we show that relative to conventional hidden Markov modeling with single-frame unvarying dFNC summary states, EVOdFNCs are more sensitive to positive symptoms of schizophrenia including hallucinations and delusions, suggesting that a more dynamic characterization is needed to help illuminate such a complex brain disorder.

Abnormal Large-Scale Neuronal Network in High Myopia.

AimResting state functional magnetic resonance imaging (rs-fMRI) was used to analyze changes in functional connectivity (FC) within various brain networks and functional network connectivity (FNC) among various brain regions in patients with high myopia (HM).Methodsrs-fMRI was used to scan 82 patients with HM (HM group) and 59 healthy control volunteers (HC group) matched for age, sex, and education level. Fourteen resting state networks (RSNs) were extracted, of which 11 were positive. Then, the FCs and FNCs of RSNs in HM patients were examined by independent component analysis (ICA).ResultsCompared with the HC group, FC in visual network 1 (VN1), dorsal attention network (DAN), auditory network 2 (AN2), visual network 3 (VN3), and sensorimotor network (SMN) significantly increased in the HM group. FC in default mode network 1 (DMN1) significantly decreased. Furthermore, some brain regions in default mode network 2 (DMN2), default mode network 3 (DMN3), auditory network 1 (AN1), executive control network (ECN), and significance network (SN) increased while others decreased. FNC analysis also showed that the network connection between the default mode network (DMN) and cerebellar network (CER) was enhanced in the HM group.ConclusionCompared with HCs, HM patients showed neural activity dysfunction within and between specific brain networks, particularly in the DMN and CER. Thus, HM patients may have deficits in visual, cognitive, and motor balance functions.

The Neuro-Endo-Microbio-Ome Study: A Pilot Study of Neurobiological Alterations Pre- Versus Post-Bariatric Surgery.

Plausible phenotype mechanisms following bariatric surgery include changes in neural and gastrointestinal physiology. This pilot study aims to investigate individual and combined neurologic, gut microbiome, and plasma hormone changes pre- versus post-vertical sleeve gastrectomy (VSG), Roux-en-Y gastric bypass (RYGB), and medical weight loss (MWL). We hypothesized post-weight loss phenotype would be associated with changes in central reward system brain connectivity, differences in postprandial gut hormone responses, and increased gut microbiome diversity. Subjects included participants undergoing VSG, n = 7; RYGB, n = 9; and MWL, n = 6. Ghrelin, glucagon-like peptide-1, peptide-YY, gut microbiome, and resting state functional magnetic resonance imaging (rsfMRI; using fractional amplitude of low-frequency fluctuations [fALFF]) were measured pre- and post-intervention in fasting and fed states. We explored phenotype characterization using clustering on gut hormone, microbiome, and rsfMRI datasets and a combined analysis. We observed more widespread fALFF differences post-bariatric surgery versus post-MWL. Decreased post-prandial fALFF was seen in food reward regions post-RYGB. The highest number of microbial taxa that increased post-intervention occurred in the RYGB group, followed by VSG and MWL. The combined hormone, microbiome, and MRI dataset most accurately clustered samples into pre- versus post-VSG phenotypes followed by RYGB subjects. The data suggest surgical weight loss (VSG and RYGB) has a bigger impact on brain and gut function versus MWL and leads to lesser post-prandial activation of food-related neural circuits. VSG subjects had the greatest phenotype differences in interactions of microbiome, rsfMRI, and gut hormone features, followed by RYGB and MWL. These results will inform future prospective research studying gut-brain changes post-bariatric surgery.

Regional Homogeneity in Patients With Mild Cognitive Impairment: A Resting-State Functional Magnetic Resonance Imaging Study.

ObjectiveTo analyze the potential changes in brain neural networks in resting state functional magnetic resonance imaging (rs-fMRI) scans by regional homogeneity (ReHo) in patients with mild cognitive impairment (MCI).MethodsWe recruited and selected 24 volunteers, including 12 patients (6 men and 6 women) with MCI and 12 healthy controls matched by age, sex, and lifestyle. All subjects were examined with rs-fMRI to evaluate changes in neural network connectivity, and the data were analyzed by ReHo method. Correlation analysis was used to investigate the relationship between ReHo values and clinical features in different brain regions of MCI patients. The severity of MCI was determined by the Mini-Mental State Examination (MMSE) scale.ResultsThe signals of the right cerebellum areas 4 and 5, left superior temporal, right superior temporal, left fusiform, and left orbital middle frontal gyri in the patient group were significantly higher than those in the normal group (P < 0.01 by t-test of paired samples). The signal intensity of the right inferior temporal and left inferior temporal gyri was significantly lower than that of the normal group (P < 0.01). The ReHO value for the left inferior temporal gyrus correlated negatively with disease duration, and the value for the right inferior temporal gyrus correlated positively with MMSE scores.ConclusionMild cognitive impairment in patients with pre- Alzheimer’s disease may be related to the excitation and inhibition of neural networks in these regions. This may have a certain guiding significance for clinical diagnosis.

P 64 Evaluation of cortical reorganization in patients with facial palsy by navigated transcranial magnetic stimulation (nTMS) and functional MRI

Background: Bell’s palsy develops due to a lesion of the facial nerve and might occur idiopathic, as a result of masses in the cerebello-pontine angle or brainstem or as a result of trauma or surgery. This prospective study aims to evaluate cortical reorganization after facial nerve palsy by means of navigated transcranial magnetic stimulation (nTMS), diffusion tensor imaging (DTI) and resting state functional magnetic resonance imaging (rsfMRI). Methods: The study is based on a prospective patient and healthy subject cohort study. The patient group consist mainly of patients with tumors of the cerebello pontine angle suffering from a postoperative facial nerve palsy. The House & Brackmann scale, and Sunnybrook scale were used to assess the facial nerve function. The cortical excitability of the facial network was determined by navigated transcranial magnetic stimulation (nTMS) with the following parameters: Resting motor threshold (RMT), Recruitment curve (RC), Cortical silent period (CSP) and Motor area. By means of functional and diffusion MRI corticobulbar tract integrity and interhemispheric connectivity were displayed. Results: We present the first results of our ongoing trial. In these two patients we were able to detect a reduced cortical excitability expressed by an increased RMT interhemispheric ration (1,3; 0,6). The facial motor area of the affected hemisphere was reduced in size (218 mm2 vs. 355,1 mm2) and there was a diminished interhemispheric connectivity (pFWE (corr) = 0.03) Conclusion: By better characterization of neuronal recovery, risk groups of patients without clinical improvement can be defined early. This gives this group a better chance to receive early surgical facial nerve reconstruction, therefore resulting in a better functional outcome. Furthermore, evaluation of cortical excitability and representation of the facial motor network after surgery might also display postoperative recovery.

Visual expertise modulates baseline brain activity: a preliminary resting-state fMRI study using expertise model of radiologists

Backgroundvisual expertise and experience modulate evoked brain activity in response to training-related stimuli. However, few studies have considered how the visual experience is represented in the resting state brain activity. This study tried to investigate the way visual experience, i.e., visual recognition expertise, modulates baseline brain neuronal activity in the resting state using the model of radiologists.MethodsThe amplitude of low-frequency (< 0.08 Hz) fluctuation (ALFF) was used as the metric of baseline brain activity and a visual expertise model of radiologists to investigated this question. The visual recognition skill enables them to accurately identify pathological information in medical images. After the behavior measurement, a cohort group of radiology interns (n = 22) and a group of matched layperson (n = 22) were selected for inclusion in the study. The resting state functional magnetic resonance imaging (fMRI) scans were performed for all of the subjects.ResultsHigher ALFF in the right fusiform gyrus and the left orbitofrontal cortex were observed, and the ALFF in the fusiform gyrus was correlated with the intern radiologists’ behavioral expertise(all results corrected for multiple comparisons).ConclusionsVisual experience modulates the baseline brain activity in both high-level visual cortex and high-order cognitive cortex, indicating the engagement of both top-down and bottom-up facilitation. We provide a novel perspective to how visual experience modulated cortical brain activity by introducing the resting state changes. Also, we propose that our current study may provide novel ideas for the development of new training protocols in medical school.

Characteristics of the Fractional Amplitude of Low-Frequency Fluctuation in Ocular Hypertension Patients: A Resting-State fMRI Study.

BackgroundThe fractional amplitude of low-frequency fluctuation (fALFF) method has been underutilized in research on the pathogenesis and clinical manifestations of ocular hypertension (OH).PurposeThis study uses resting state functional magnetic resonance imaging (rs-fMRI) and fALFF to investigate the nature of spontaneous brain activity in OH patients and the relationship, if any, between changes in activity and clinical features.Materials and MethodsA total of 18 subjects (9 females and 9 males) with ocular hypertension (OH) and 18 healthy controls (HCs) matched for gender, age, and educational level were recruited to this study. All participants underwent an rs-fMRI scan, and spontaneous brain activity was assessed using the fALFF method. Receiver operating characteristic curves were plotted to investigate differences between OH and HC groups.ResultsThe fALFF values of OH patients were significantly higher in the left precuneus lobe (LP), compared with the same region in controls (P < 0.05). Conversely, values in the left anterior cingulate lobe (LAC), were significantly lower (P < 0.05) in OH than in controls. However, no significant association was found between the mean fALFF values and clinical characteristics in either brain area.ConclusionHigh spontaneous activity in two brain areas may reflect neuropathological mechanisms underpinning visual impairment in OH patients.

Deep learning resting state functional magnetic resonance imaging lateralization of temporal lobe epilepsy.

Localization of focal epilepsy is critical for surgical treatment of refractory seizures. There remains a great need for noninvasive techniques to localize seizures for surgical decision-making. We investigate the use of deep learning using resting state functional magnetic resonance imaging (RS-fMRI) to identify the hemisphere of seizure onset in temporal lobe epilepsy (TLE) patients. A total of 2132 healthy controls and 32 preoperative TLE patients were studied. All participants underwent structural MRI and RS-fMRI. Healthy control data were used to generate training samples for a three-dimensional convolutional neural network (3DCNN). RS-fMRI was synthetically altered in randomly lateralized regions in the healthy control participants. The model was then trained to classify the hemisphere containing synthetic noise. Finally, the model was tested on TLE patients to assess its performance for detecting biological seizure onset zones, and gradient-weighted class activation mapping (Grad-CAM) identified the strongest predictive regions. The 3DCNN classified healthy control hemispheres known to contain synthetic noise with 96% accuracy, and TLE hemispheres clinically identified to be seizure onset zones with 90.6% accuracy. Grad-CAM identified a range of temporal, frontal, parietal, and subcortical regions that were strong anatomical predictors of the seizure onset zone, and the resting state networks that colocalized with Grad-CAM results included default mode, medial temporal, and dorsal attention networks. Lastly, in an analysis of a subset of patients with postsurgical outcomes, the 3DCNN leveraged a more focal set of regions to achieve classification in patients with Engel Class >I compared to Engel Class I. Noninvasive techniques capable of localizing the seizure onset zone could improve presurgical planning in patients with intractable epilepsy. We have demonstrated the ability of deep learning to identify the correct hemisphere of the seizure onset zone in TLE patients using RS-fMRI with high accuracy. This approach represents a novel technique of seizure lateralization that could improve preoperative surgical planning.

348 Resting state fMRI connectivity in individuals with aphasia and the role of the inferior frontal gyrus

OBJECTIVES/GOALS: This poster will explore lesion-symptom mapping and resting state functional magnetic resonance imaging (rsfMRI) in participants with aphasia. This analysis aims to reveal the behavioral impact of distinct lesions to the left inferior frontal gyrus (LIFG) and the potential for rsfMRI to provide evidence of cortical reorganization. METHODS/STUDY POPULATION: The analyses will be conducted on a small sample of approximately six participants with post-stroke language impairment (i.e., aphasia) recruited as part of an ongoing study. Lesion load in the anterior LIFG (aLIFG), consisting of the orbital (BA 47) and triangular (BA 45) parts, and the posterior LIFG (pLIFG), consisting of the opercular part (BA 44) will be correlated with performance on tasks of semantic and phonological processing. Functional connectivity will be determined between regions of interest (i.e., anterior superior temporal, posterior middle temporal, angular, and supramarginal gyri) in the left and/or right hemispheres based on rsfMRI data. RESULTS/ANTICIPATED RESULTS: Lesion load in the aLIFG is expected to correlate to performance on the semantic task, whereas lesion load in the pLIFG is expected to correlate to performance on the phonological task. For participants whose behavioral performance exceeds expectations based on lesion load (e.g., larger aLIFG lesion load, yet better semantic task performance), rsfMRI connectivity is expected to be greater (e.g., between the posterior middle temporal and angular gyri), suggesting cortical reorganization. DISCUSSION/SIGNIFICANCE: If our hypotheses are supported, our results will corroborate evidence of a functional spectrum (i.e., semantic-phonological) in the LIFG. Future work will compare rsfMRI connectivity to neurotypical controls and sites of connectivity may be used as targets in studies of non-invasive brain stimulation as an adjuvant to behavioral therapy.

Resting State MRI Amplitude of Low Frequency Fluctuations Associated With Suicidal Ideation in Bipolar Depression.

Objective: Suicidal ideation (SI) is a risk factor for completed suicide. Our previous resting state functional magnetic resonance imaging (fMRI) study found that higher amplitude of low frequency fluctuation (ALFF) in right hippocampus and thalamus was associated with SI in major depressive disorder (MDD). The present study aimed to evaluate that association in participants with bipolar disorder (BD).Methods: Thirty depressed, adult participants with a DSM-IV diagnosis of BD had resting state fMRI scans. Region-of-interest (ROI) analyses used ALFF values within areas that were previously associated with SI in MDD. Spearman rank correlation and ordinal regression analyses were performed to assess associations between ALFF values and the SI item of the Montgomery-Asberg Depression Rating Scale. Exploratory whole-brain analyses identified regions where ALFF was associated with SI.Results: Within the right hippocampus region, SI was positively associated with ALFF (Spearman R = 0.490, P = .0060). Ordinal regression analysis indicated that for every 0.1-unit increase in ALFF in that region, the odds of having higher SI were increased by 35% (odds ratio = 1.35; 95% confidence interval, 1.08-1.73; P = .012). Within the previously identified thalamus cluster, SI was associated with ALFF only at a trend level (Spearman R = 0.310, P = .069). Whole-brain analyses identified 3 clusters of positive association between SI and ALFF, 1 of which was located in the right hippocampus.Conclusions: This study found that our previous finding of positive association between SI and ALFF in the right hippocampus extended to bipolar depression. Future studies should examine the clinical utility of this association, and the role of the hippocampus in SI.Trial Registration: Data used for this secondary analysis came from studies with ClinicalTrials.gov identifiers NCT02239094 (January 2015 through September 2016) and NCT02473250 (January 2015 through December 2019).

The Modifying of Functional Connectivity Induced by Peripheral Nerve Field Stimulationusing Electroacupuncture for Migraine: A Prospective Clinical Study.

We examined the functional connectivity (FC) in patients with migraine compared with healthy subjects before and after C2 peripheral nerve field stimulation with electroacupuncture (EA-C2-PNfS) to evaluate the effect of EA-C2-PNfS and elucidate the mechanism of migraine. Twenty-six patients with migraine and 24 healthy controls were recruited. All patients underwent resting state functional magnetic resonance imaging before and after 3 months of EA-C2-PNfS. We evaluated a numerical rating scale, the Headache Impact Test, and the Self-Rating Depression Scale, which assesses depression. Healthy controls underwent magnetic resonance imaging twice at a 3-month interval without acupuncture. An analysis of FC in the region of interest in the pain matrix was performed. Twenty patients with migraine and 23 healthy controls (mean ± standard deviation: 44.9 ± 12.9 years of age) were included. Three patients had migraine with aura (55.0 ± 18.0 years of age), 11 patients had migraine without aura (MWoA) (45.6 ± 14.6 years of age), and six patients had chronic migraine (40.8 ± 13.9 years of age). The clinical assessments significantly improved after EA-C2-PNfS in the MWoA group only. In FC analysis, the MWoA group showed a significant decrease after EA-C2-PNfS in FC between the right hypothalamus and left insula. Right hypothalamus-related FC was lower before acupuncture in the chronic migraine group than in the MWoA group. After EA-C2-PNfS for MWoA, significant changes in FC were observed at the hypothalamus and insula. Our results indicate that EA-C2-PNfS could improve migraine headache by modifying pain-related FC.

Covariance and Correlation Analysis of Resting State Functional Magnetic Resonance Imaging Data Acquired in a Clinical Trial of Mindfulness-Based Stress Reduction and Exercise in Older Individuals.

We describe and apply novel methodology for whole-brain analysis of resting state fMRI functional connectivity data, combining conventional multi-channel Pearson correlation with covariance analysis. Unlike correlation, covariance analysis preserves signal amplitude information, which feature of fMRI time series may carry physiological significance. Additionally, we demonstrate that dimensionality reduction of the fMRI data offers several computational advantages including projection onto a space of manageable dimension, enabling linear operations on functional connectivity measures and exclusion of variance unrelated to resting state network structure. We show that group-averaged, dimensionality reduced, covariance and correlation matrices are related, to reasonable approximation, by a single scalar factor. We apply this methodology to the analysis of a large, resting state fMRI data set acquired in a prospective, controlled study of mindfulness training and exercise in older, sedentary participants at risk for developing cognitive decline. Results show marginally significant effects of both mindfulness training and exercise in both covariance and correlation measures of functional connectivity.

Functional Brain Connectivity in Mild Cognitive Impairment With Sleep Disorders: A Study Based on Resting-State Functional Magnetic Resonance Imaging.

PurposeTo investigate the effect of sleep disorder (SD) on the changes of brain network dysfunction in mild cognitive impairment (MCI), we compared network connectivity patterns among MCI, SD, and comorbid MCI and sleep disorders (MCI-SD) patients using resting state functional magnetic resonance imaging (RS-fMRI).Patients and MethodsA total of 60 participants were included in this study, 20 each with MCI, SD, or MCI-SD. And all participants underwent structural and functional MRI scanning. The default-mode network (DMN) was extracted by independent component analysis (ICA), and regional functional connectivity strengths were calculated and compared among groups.ResultsCompared to MCI patients, The DMN of MCI-SD patients demonstrated weaker functional connectivity with left middle frontal gyrus, right superior marginal gyrus, but stronger connectivity with the left parahippocampus, left precuneus and left middle temporal gyrus. Compared to the SD group, MCI-SD patients demonstrated weaker functional connectivity with right transverse temporal gyrus (Heschl’s gyrus), right precentral gyrus, and left insula, but stronger connectivity with posterior cerebellum, right middle occipital gyrus, and left precuneus.ConclusionPatients with MCI-SD show unique changes in brain network connectivity patterns compared to MCI or SD alone, likely reflecting a broader functional disconnection and the need to recruit more brain regions for functional compensation.

Pediatric Exposures to Neurotoxicants: A Review of Magnetic Resonance Imaging and Spectroscopy Findings.

Heavy metals, including lead and manganese, air pollution, pesticides, environmental tobacco smoke, and flame retardants are among the known and suspected environmental neurotoxicant exposures examined with magnetic resonance imaging (MRI)-based studies of pediatric populations. Many studies feature morphological changes associated with the exposures while others employ magnetic resonance spectroscopy, diffusion imaging, task-based, and resting state functional magnetic resonance imaging to reveal abnormal metabolic concentrations, white matter disorganization, and atypical patterns of activation. Some studies follow pregnant women and their offspring throughout the lifespan with collection of individual specimens as exposure biomarkers. Others innovatively make use of public databases to obtain relevant exposure biomarkers while taking advantage of these studies in their efforts to monitor developmental features in large, population-based, imaging cohorts. As exposures to neurotoxicants in the womb and throughout childhood have life-long impacts on health and well-being, the importance of these innovative neuroimaging investigations is ever increasing.

Multimodal Magnetic Resonance Imaging Reveals Aberrant Brain Age Trajectory During Youth in Schizophrenia Patients.

Accelerated brain aging had been widely reported in patients with schizophrenia (SZ). However, brain aging trajectories in SZ patients have not been well-documented using three-modal magnetic resonance imaging (MRI) data. In this study, 138 schizophrenia patients and 205 normal controls aged 20–60 were included and multimodal MRI data were acquired for each individual, including structural MRI, resting state-functional MRI and diffusion tensor imaging. The brain age of each participant was estimated by features extracted from multimodal MRI data using linear multiple regression. The correlation between the brain age gap and chronological age in SZ patients was best fitted by a positive quadratic curve with a peak chronological age of 47.33 years. We used the peak to divide the subjects into a youth group and a middle age group. In the normal controls, brain age matched chronological age well for both the youth and middle age groups, but this was not the case for schizophrenia patients. More importantly, schizophrenia patients exhibited increased brain age in the youth group but not in the middle age group. In this study, we aimed to investigate brain aging trajectories in SZ patients using multimodal MRI data and revealed an aberrant brain age trajectory in young schizophrenia patients, providing new insights into the pathophysiological mechanisms of schizophrenia.

Amplitude of Low-Frequency Oscillations in First-Episode Drug-Naive Patients with Major Depressive Disorder: A Resting State Functional Magnetic Resonance Imaging Study.

ObjectiveTo observe characteristics of the amplitudes of low-frequency oscillation (LFO) in first-episode drug-naive patients with major depressive disorder (MDD).MethodsAmplitudes of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) were computed using resting-state functional magnetic resonance imaging (rs-fMRI) data of 39 first-episode drug-naive patients with MDD and 37 healthy controls.ResultsALFF and fALFF in the left cerebellum were significantly higher in patients with MDD compared to control group, while ALFF in the right rolandic operculum was significantly lower (all p < 0.001, AlphaSim correction).ConclusionAbnormal neurological activity in multiple brain regions in first-episode drug-naive patients with MDD may be involved in the neurobiological mechanisms of MDD and should be considered in future studies.

Aberrant functional connectivity in insular subregions in somatic depression: a resting-state fMRI study

BackgroundSomatic depression (SD) is different from non-somatic depression (NSD), and insular subregions have been associated with somatic symptoms. However, the pattern of damage in the insular subregions in SD remains unclear. The aim of this study was to use functional connectivity (FC) analyses to explore the bilateral ventral anterior insula (vAI), bilateral dorsal anterior insula (dAI), and bilateral posterior insula (PI) brain circuits in SD patients.MethodsThe study included 28 SD patients, 30 NSD patients, and 30 matched healthy control (HC) subjects. All participants underwent 3.0 T resting state functional magnetic resonance imaging. FC analyses were used to explore synchronization between insular subregions and the whole brain in the context of depression with somatic symptoms. Pearson correlation analyses were performed to assess relationships between FC values in brain regions showing significant differences and the total and factor scores on the 17-item Hamilton Rating Scale for Depression (HAMD17).ResultsCompared with the NSD group, the SD group showed significantly decreased FC between the left vAI and the right rectus gyrus, right fusiform gyrus, and right angular gyrus; between the right vAI and the right middle cingulate cortex, right precuneus, and right superior frontal gyrus; between the left dAI and the left fusiform gyrus; and between the right dAI and the left postcentral gyrus. Relative to the NSD group, the SD group exhibited increased FC between the left dAI and the left fusiform gyrus. There were no differences in FC between bilateral PI and any brain regions among the SD, NSD, and HC groups. Within the SD group, FC values between the left vAI and right rectus gyrus were positively correlated with cognitive impairment scores on the HAMD17; FC values between the right vAI and right superior frontal gyrus were positively related to the total scores and cognitive impairment scores on the HAMD17 (p < 0.05, uncorrected).ConclusionsAberrant FC between the anterior insula and the frontal and limbic cortices may be one possible mechanism underlying SD.

Altered resting fMRI spectral power in data-driven brain networks during development: A longitudinal study

BackgroundLongitudinal studies provide a more precise measure of brain development over time, as they focus on within subject variability, as opposed to cross-sectional studies. This is especially important in children, where rapid brain development occurs, and inter-subject variability can be large. Tracking healthy brain development and identifying markers of typical development are also critically important to diagnose mental disorders at early ages. New methodWe track longitudinal changes in spectral power of time-courses using a unique non-binning approach assessed with group independent component analysis, in a large multi time-point resting state functional magnetic resonance imaging dataset (N = 124) containing healthy children from 8.2 to 17.6 years old (m=12.6) called the Developmental Chronnecto-Genomics study. We examined how eyes open (EO) and eyes closed (EC) resting states play a role in age-related spectral differences, as several studies have reported differences in these conditions. ResultsTypical brain development shows increased spectral power in low frequencies and decreased spectral power in high frequencies in as children grow and develop, for both the EO and EC conditions. In addition, we observed significant differences in power spectra between EO and EC and between sexes, mainly suggesting higher spectral power in females at middle and high frequencies. A replication analysis using the Adolescent Brain Cognitive Development data (N = 3371, mean age 9.9 years old) further supported this result, also showing general increases in low frequencies and decreases in higher frequencies, though some network level differences are present comparing to the main dataset. Comparison with existing methodOur results indicate that spectral power changes significantly with typical development and our non-binning approach shows these changes with more detailed frequency resolution comparing to binning approaches. This is important as many studies reported an association of higher frequency power with brain disorders. ConclusionOur findings of decreased spectral power in the high frequencies with development may be a general marker of typical development., though this needs further investigation.