Brain Network Connectivity Research Articles

Quantifying Apathy in Late-Life Depression: Unraveling Neurobehavioral Links Through Daily Activity Patterns and Brain Connectivity Analysis

BackgroundBetter understanding apathy in late-life depression would help improve prediction of poor prognosis of diseases such as dementia. Actimetry provides an objective and ecological measure of apathy from patients’ daily motor activity. We aimed to determine whether patterns of motor activity were associated with apathy and brain connectivity in networks that underlie goal-directed behaviors. MethodsResting-state functional magnetic resonance imaging and diffusion magnetic resonance imaging were collected from 38 nondemented participants with late-life depression. Apathy was evaluated using the diagnostic criteria for apathy, Apathy Evaluation Scale, and Apathy Motivation Index. Functional principal components (fPCs) of motor activity were derived from actimetry recordings taken for 72 hours. Associations between fPCs and apathy were estimated by linear regression. Subnetworks whose connectivity was significantly associated with fPCs were identified via threshold-free network-based statistics. The relationship between apathy and microstructure metrics was estimated along fibers by diffusion tensor imaging and a multicompartment model called neurite orientation dispersion and density imaging via tractometry. ResultsWe found 2 fPCs associated with apathy: mean diurnal activity, negatively associated with Apathy Evaluation Scale scores, and an early chronotype, negatively associated with Apathy Motivation Index scores. Mean diurnal activity was associated with increased connectivity in the default mode, cingulo-opercular, and frontoparietal networks, while chronotype was associated with a more heterogeneous connectivity pattern in the same networks. We did not find significant associations between microstructural metrics and fPCs. ConclusionsOur findings suggest that mean diurnal activity and chronotype could provide indirect ambulatory measures of apathy in late-life depression, associated with modified functional connectivity of brain networks that underlie goal-directed behaviors.

The contribution of EEG to assess and treat motor disorders in multiple sclerosis

ObjectiveElectroencephalography (EEG) can highlight significant changes in spontaneous electrical activity of the brain produced by altered brain network connectivity linked to inflammatory demyelinating lesions and neuronal loss occurring in multiple sclerosis (MS). In this review, we describe the main EEG findings reported in the literature to characterize motor network alteration in term of local activity or functional connectivity changes in patients with MS (pwMS). MethodsA comprehensive literature search was conducted to include articles with quantitative analyses of resting-state EEG recordings (spectrograms or advanced methods for assessing spatial and temporal dynamics, such as coherence, theory of graphs, recurrent quantification, microstates) or dynamic EEG recordings during a motor task, with or without connectivity analyses. ResultsIn this systematic review, we identified 26 original articles using EEG in the evaluation of MS-related motor disorders. Various resting or dynamic EEG parameters could serve as diagnostic biomarkers of motor control impairment to differentiate pwMS from healthy subjects or be related to a specific clinical condition (fatigue) or neuroradiological aspects (lesion load). ConclusionsWe highlight some key EEG patterns in pwMS at rest and during movement, both suggesting an alteration or disruption of brain connectivity, more specifically involving sensorimotor networks. SignificanceSome of these EEG biomarkers of motor disturbance could be used to design future therapeutic strategies in MS based on neuromodulation approaches, or to predict the effects of motor training and rehabilitation in pwMS.

106 Characteristics of Cognitive Impairment in Moyamoya Disease

INTRODUCTION: Cognitive impairment in adult moyamoya disease (MMD) is thought to be the result of ischemic stroke; however, the presence and extent of cognitive decline in asymptomatic patients remain largely unknown. METHODS: After classification using T2-weighted fluid attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI), a total of 19 MMD patients with a history of cerebral infarction, 21 asymptomatic MMD patients, and 20 healthy controls matched for age, sex, and years of education were prospectively included in this study. A detailed neuropsychological evaluation of two moyamoya subgroups and normal controls was conducted. In addition, participants underwent arterial spin labeling and resting state fMRI sequences. RESULTS: Asymptomatic patients showed varying degrees of decline in intelligence (Raven’s Standard Progressive Matrices, P = 0.001), spatial imagination (mental rotation, P = 0.014), working memory (verbal working memory-backward digit span, P = 0.011), and computational ability (simple subtraction, P = 0.014; complex subtraction, P < 0.001) compared with normal controls. MMD patients with cerebral infarction had more severe impairment in complex arithmetic (P = 0.027) and word short-term memory (P = 0.01) than those without symptoms. The asymptomatic MMD group also showed decreased CBF in the left anterior central and left inferior frontal gyri of the island fap with multiple node abnormalities in the brain network and reduced network connectivity. There was a significant association of these changes with cognitive decline in the MMD group. CONCLUSIONS: In asymptomatic MMD patients, a variety of cognitive impairments precedes the onset of clinical symptoms such as cerebral infarction, which may be a long-term complication of conservative treatment. Besides, disturbance of CBF and impaired brain network connections may be important causes of cognitive decline.

Specialization of amygdala subregions in emotion processing.

The amygdala is important for human fear processing. However, recent research has failed to reveal specificity, with evidence that the amygdala also responds to other emotions. A more nuanced understanding of the amygdala's role in emotion processing, particularly relating to fear, is needed given the importance of effective emotional functioning for everyday function and mental health. We studied 86 healthy participants (44 females), aged 18-49 (mean 26.12 ± 6.6) years, who underwent multiband functional magnetic resonance imaging. We specifically examined the reactivity of four amygdala subregions (using regions of interest analysis) and related brain connectivity networks (using generalized psycho-physiological interaction) to fear, angry, and happy facial stimuli using an emotional face-matching task. All amygdala subregions responded to all stimuli (p-FDR < .05), with this reactivity strongly driven by the superficial and centromedial amygdala (p-FDR < .001). Yet amygdala subregions selectively showed strong functional connectivity with other occipitotemporal and inferior frontal brain regions with particular sensitivity to fear recognition and strongly driven by the basolateral amygdala (p-FDR < .05). These findings suggest that amygdala specialization to fear may not be reflected in its local activity but in its connectivity with other brain regions within a specific face-processing network.

Strength of spatial correlation between gray matter connectivity and patterns of proto-oncogene and neural network construction gene expression is associated with diffuse glioma survival.

Like other forms of neuropathology, gliomas appear to spread along neural pathways. Accordingly, our group and others have previously shown that brain network connectivity is highly predictive of glioma survival. In this study, we aimed to examine the molecular mechanisms of this relationship via imaging transcriptomics. We retrospectively obtained presurgical, T1-weighted MRI datasets from 669 adult patients, newly diagnosed with diffuse glioma. We measured brain connectivity using gray matter networks and coregistered these data with a transcriptomic brain atlas to determine the spatial co-localization between brain connectivity and expression patterns for 14 proto-oncogenes and 3 neural network construction genes. We found that all 17 genes were significantly co-localized with brain connectivity (p < 0.03, corrected). The strength of co-localization was highly predictive of overall survival in a cross-validated Cox Proportional Hazards model (mean area under the curve, AUC = 0.68 +/- 0.01) and significantly (p < 0.001) more so for a random forest survival model (mean AUC = 0.97 +/- 0.06). Bayesian network analysis demonstrated direct and indirect causal relationships among gene-brain co-localizations and survival. Gene ontology analysis showed that metabolic processes were overexpressed when spatial co-localization between brain connectivity and gene transcription was highest (p < 0.001). Drug-gene interaction analysis identified 84 potential candidate therapies based on our findings. Our findings provide novel insights regarding how gene-brain connectivity interactions may affect glioma survival.

Dissociable Contributions of the Medial Parietal Cortex to Recognition Memory.

Human neuroimaging studies of episodic memory retrieval routinely observe the engagement of specific cortical regions beyond the medial temporal lobe. Of these, medial parietal cortex (MPC) is of particular interest given its distinct functional characteristics during different retrieval tasks. Specifically, while recognition and autobiographical recall tasks are both used to probe episodic retrieval, these paradigms consistently drive distinct spatial patterns of response within MPC. However, other studies have emphasized alternate MPC functional dissociations in terms of brain network connectivity profiles or stimulus category selectivity. As the unique contributions of MPC to episodic memory remain unclear, adjudicating between these different accounts can provide better consensus regarding MPC function. Therefore, we used a precision-neuroimaging dataset (7T functional magnetic resonance imaging) to examine how MPC regions are differentially engaged during recognition memory and how these task-related dissociations may also reflect distinct connectivity and stimulus category functional profiles. We observed interleaved, though spatially distinct, subregions of MPC where responses were sensitive to either recognition decisions or the semantic representation of stimuli. In addition, this dissociation was further accentuated by functional subregions displaying distinct profiles of connectivity with the hippocampus during task and rest. Finally, we show that recent observations of dissociable person and place selectivity within the MPC reflect category-specific responses from within identified semantic regions that are sensitive to mnemonic demands. Together, by examining precision functional mapping within individuals, these data suggest that previously distinct observations of functional dissociation within MPC conform to a common principle of organization throughout hippocampal-neocortical memory systems.

Graph theoretical analysis and independent component analysis of diabetic optic neuropathy: A resting-state functional magnetic resonance imaging study.

This study aimed to investigate the resting-state functional connectivity and topologic characteristics of brain networks in patients with diabetic optic neuropathy (DON). Resting-state functional magnetic resonance imaging scans were performed on 23 patients and 41 healthy control (HC) subjects. We used independent component analysis and graph theoretical analysis to determine the topologic characteristics of the brain and as well as functional network connectivity (FNC) and topologic properties of brain networks. Compared with HCs, patients with DON showed altered global characteristics. At the nodal level, the DON group had fewer nodal degrees in the thalamus and insula, and a greater number in the right rolandic operculum, right postcentral gyrus, and right superior temporal gyrus. In the internetwork comparison, DON patients showed significantly increased FNC between the left frontoparietal network (FPN-L) and ventral attention network (VAN). Additionally, in the intranetwork comparison, connectivity between the left medial superior frontal gyrus (MSFG) of the default network (DMN) and left putamen of auditory network was decreased in the DON group. DON patients altered node properties and connectivity in the DMN, auditory network, FPN-L, and VAN. These results provide evidence of the involvement of specific brain networks in the pathophysiology of DON.

The Emotion Regulation of Acupuncture in Chronic Low Back Pain: A Clinical Neuroimaging Protocol.

Acupuncture is effective for patients with chronic low back pain (CLBP), which can relieve pain intensity and regulate negative emotional states such as pain-related anxiety and depression. Previous studies mainly discuss the analgesic mechanism of acupuncture treatment of CLBP, but there are multiple dimensions to pain, including sensation, emotion and cognition. Therefore, this study aims to investigate the central mechanism of acupuncture for CLBP from the perspective of emotional regulation by functional magnetic resonance imaging (fMRI). A total of 72 patients with CLBP will be recruited in the study and randomly assigned to the verum acupuncture group or the sham acupuncture group. The trail will last for 18 weeks including a 2-week baseline, a 4-week treatment and a 12-week for follow-up period. The primary outcomes are the visual analog scale (VAS) and the Japanese Orthopaedic Association Scores (JOA) score. The secondary outcomes are the 12-item short form health survey (SF-12), the state trait anxiety inventory (STAI), the self-rating anxiety scale (SAS) and self-rating depression scale (SDS). The VAS, JOA, STAI SAS and SDS will be collected at baseline, week 2, week 4, and after follow-up. The SF-12 will be evaluated at baseline, week 2 and week 4. Functional magnetic resonance imaging (MRI) data will be collected at baseline and the end of treatment. Emotion-related brain regions will be chosen as regions of interest (ROIs). The gray matter volume (GMV), amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), functional connectivity (FC), and large-scale functional brain network based on these ROIs will be analyzed within and between the two groups. This study will verify the emotional regulation of acupuncture and explore the mechanism of acupuncture for emotion regulation in patients with CLBP. https://www.chictr.org.cn/showproj.html?proj=195486, identifier: ChiCTR2300070557.

Efficacy of transcranial photobiomodulation in the treatment for major depressive disorder: A TMS-EEG and pilot study.

Major depressive disorder (MDD) was a prevalent mental condition that may be accompanied by decreased excitability of left frontal pole (FP) and abnormal brain connections. An 820 nm tPBM can induce an increase in stimulated cortical excitability. The purpose of our study was to establish how clinical symptoms and time-varying brain network connectivity of MDD were affected by transcranial photobiomodulation (tPBM). A total of 11 patients with MDD received 820 nm tPBM targeting the left FP for 14 consecutive days. The severity of symptoms was evaluated by neuropsychological assessments at baseline, after treatment, 4-week and 8-week follow-up; 8-min transcranial magnetic stimulation combined electroencephalography (TMS-EEG) was performed for five healthy controls and five patients with MDD before and after treatment, and time-varying EEG network was analyzed using the adaptive-directed transfer function. All of scales scores in the 11 patients decreased significantly after 14-day tPBM (p < .01) and remained at 8-week follow-up. The time-varying brain network analysis suggested that the brain regions with enhanced connection information outflow in MDD became gradually more similar to healthy controls after treatment. This study showed that tPBM of the left FP could improve symptoms of patients with MDD and normalize the abnormal network connections.

Measurement of Functional Brain Network Connectivity in People with Orthostatic Tremor.

Orthostatic tremor is a rare movement disorder characterized by a sensation of unsteadiness and leg tremor while standing. It has been hypothesized that the disorder is attributable to dysregulation of a central oscillatory network in the brain. This putative network includes primary motor cortex, supplementary motor area, cerebellum, thalamus, and pontine tegmentum. We studied this brain network by recording resting-state functional MRI data from individuals with orthostatic tremor. For each participant, we measured resting-state functional connectivity using a seed-based approach. Regions of interest included were components of the putative central oscillatory network and a primary motor thumb region (identified via transcranial magnetic stimulation). A non-central oscillatory network region of interest-posterior cingulate cortex-was included for comparative analysis of a well-characterized intrinsic network, the default mode network. Demographic information, medical history, and tremor characteristics were collected to test associations with functional connectivity. For normative context, data from the 1000 Functional Connectomes Project were analyzed using an identical approach. We observed that tremor and demographic variables were correlated with functional connectivity of central oscillatory network components. Furthermore, relative to healthy comparison participants, patients with orthostatic tremor exhibited qualitatively different patterns of cerebellar resting state functional connectivity. Our study enhances the current understanding of brain network differences related to orthostatic tremor and is consistent with a hypothesized selective decoupling of cerebellum. Additionally, associations observed between functional connectivity and factors including medical history and tremor features may suggest targets for treatment of orthostatic tremor.

Resting-state brain network connectivity is an independent predictor of responsiveness to language therapy in chronic post-stroke aphasia

Post-stroke aphasia recovery, especially in the chronic phase, is challenging to predict. Functional integrity of the brain and brain network topology have been suggested as biomarkers of language recovery. This study sought to investigate functional connectivity in four predefined brain networks (i.e., language, default mode, dorsal attention, and salience networks), in relation to aphasia severity and response to language therapy. Thirty patients with chronic post-stroke aphasia were recruited and received a treatment targeting word finding. Structural and functional brain scans were acquired at baseline and resting state functional connectivity for each network was calculated. Additionally, graph measures quantifying network properties were calculated for each network. These included global efficiency for all networks and average strength and clustering coefficient for the language network. Linear mixed effects models showed that mean functional connectivity in the default mode, dorsal attention, and salience networks as well as graph measures of all four networks are independent predictors of response to therapy. While greater mean functional connectivity and global efficiency of the dorsal attention and salience networks predicted greater treatment response, greater mean functional connectivity and global efficiency in the default mode network predicted poorer treatment response. Results for the language network were more nuanced with more efficient network configurations (as reflected in graph measures), but not mean functional connectivity, predicting greater treatment response. These findings highlight the prognostic value of resting-state functional connectivity in chronic treatment-induced aphasia recovery.

Conectividad cerebral, empatía, insensibilidad emocional y toma de decisiones en el trastorno de la conducta: Una revisión sistemática.

The deficits in empathy, emotional insensitivity, and decision-making constitute the core of symptoms defining conduct disorder. Although several studies have established some correlates between brain connectivity and symptoms separately, there has been little effort to systematize such information. The current systematic review aimed to describe the findings obtained through analyzing brain connectivity networks by functional magnetic resonance imaging associated with alterations in empathy, emotional insensitivity, and decision-making in subjects with conduct disorder. A systematic search was carried out for original studies published in Medline (PubMed), Scopus, Scielo, Google Scholar, Scopus, and Nature. Articles published between 2000 and 2022 were included; a qualitative synthesis was obtained with the six selected articles at the end of the process. The findings show altered brain connectivity patterns in brain regions associated with empathy and insensitivity in subjects with conduct disorder.

Repetitive transcranial magnetic stimulation regulates effective connectivity patterns of brain networks in the spectrum of preclinical Alzheimer's disease.

Subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) are considered as the spectrum of preclinical Alzheimer's disease (AD), with abnormal brain network connectivity as the main neuroimaging feature. Repetitive transcranial magnetic stimulation (rTMS) has been proven to be an effective non-invasive technique for addressing neuropsychiatric disorders. This study aims to explore the potential of targeted rTMS to regulate effective connectivity within the default mode network (DMN) and the executive control network (CEN), thereby improving cognitive function. This study included 86 healthy controls (HCs), 72 SCDs, and 86 aMCIs. Among them, 10 SCDs and 11 aMCIs received a 2-week rTMS course of 5-day, once-daily. Cross-sectional analysis with the spectral dynamic causal model (spDCM) was used to analyze the DMN and CEN effective connectivity patterns of the three groups. Afterwards, longitudinal analysis was conducted on the changes in effective connectivity patterns and cognitive function before and after rTMS for SCD and aMCI, and the correlation between them was analyzed. Cross-sectional analysis showed different effective connectivity patterns in the DMN and CEN among the three groups. Longitudinal analysis showed that the effective connectivity pattern of the SCD had changed, accompanied by improvements in episodic memory. Correlation analysis indicated a negative relationship between effective connectivity from the left angular gyrus (ANG) to the anterior cingulate gyrus and the ANG.R to the right middle frontal gyrus, with visuospatial and executive function, respectively. In patients with aMCI, episodic memory and executive function improved, while the effective connectivity pattern remained unchanged. This study demonstrates that PCUN-targeted rTMS in SCD regulates the abnormal effective connectivity patterns in DMN and CEN, thereby improving cognition function. Conversely, in aMCI, the mechanism of improvement may differ. Our findings further suggest that rTMS is more effective in preventing or delaying disease progression in the earlier stages of the AD spectrum. http://www.chictr.org.cn, ChiCTR2000034533.

Brain network centrality and connectivity are associated with clinical subtypes and disease progression in Parkinson's disease.

To investigate brain network centrality and connectivity alterations in different Parkinson's disease (PD) clinical subtypes using resting-state functional magnetic resonance imaging (RS-fMRI), and to explore the correlation between baseline connectivity changes and the clinical progression. Ninety-two PD patients were enrolled at baseline, alongside 38 age- and sex-matched healthy controls. Of these, 85 PD patients underwent longitudinal assessments with a mean of 2.75 ± 0.59 years. Two-step cluster analysis integrating comprehensive motor and non-motor manifestations was performed to define PD subtypes. Degree centrality (DC) and secondary seed-based functional connectivity (FC) were applied to identify brain network centrality and connectivity changes among groups. Regression analysis was used to explore the correlation between baseline connectivity changes and clinical progression. Cluster analysis identified two main PD subtypes: mild PD and moderate PD. Two different subtypes within the mild PD were further identified: mild motor-predominant PD and mild-diffuse PD. Accordingly, the disrupted DC and seed-based FC in the left inferior frontal orbital gyrus and left superior occipital gyrus were severe in moderate PD. The DC and seed-based FC alterations in the right gyrus rectus and right postcentral gyrus were more severe in mild-diffuse PD than in mild motor-predominant PD. Moreover, disrupted DC were associated with clinical manifestations at baseline in patients with PD and predicted motor aspects progression over time. Our study suggested that brain network centrality and connectivity changes were different among PD subtypes. RS-fMRI holds promise to provide an objective assessment of subtype-related connectivity changes and predict disease progression in PD.

Brain network connectivity during peer evaluation in adolescent females: Associations with age, pubertal hormones, timing, and status

Despite copious data linking brain function with changes to social behavior and mental health, little is known about how puberty relates to brain functioning. We investigated the specificity of brain network connectivity associations with pubertal indices and age to inform neurodevelopmental models of adolescence. We examined how brain network connectivity during a peer evaluation fMRI task related to pubertal hormones (dehydroepiandrosterone and testosterone), pubertal timing and status, and age. Participants were 99 adolescents assigned female at birth aged 9–15 (M = 12.38, SD = 1.81) enriched for the presence of internalizing symptoms. Multivariate analysis revealed that within Salience, between Frontoparietal – Reward and Cinguloopercular – Reward network connectivity were associated with all measures of pubertal development and age. Specifically, Salience connectivity linked with age, pubertal hormones, and status, but not timing. In contrast, Frontoparietal – Reward connectivity was only associated with hormones. Finally, Cinguloopercular – Reward connectivity related to age and pubertal status, but not hormones or timing. These results provide evidence that the salience processing underlying peer evaluation is jointly influenced by various indices of puberty and age, while coordination between cognitive control and reward circuitry is related to pubertal hormones, pubertal status, and age in unique ways.

Sex based differences in functional connectivity during a working memory task: an fNIRS study.

Differences in corticocerebral structure and function between males and females and their effects on behavior and the prevalence of various neuropsychiatric disorders have been considered as a fundamental topic in various fields of neuroscience. Recent studies on working memory (WM) reported the impact of sex on brain connectivity patterns, which reflect the important role of functional connectivity in the sex topic. Working memory, one of the most important cognitive tasks performed by regions of the PFC, can provide evidence regarding the presence of a difference between males and females. The present study aimed to assess sex differences in brain functional connectivity during working memory-related tasks by using functional near-infrared spectroscopy (fNIRS). In this regard, nine males and nine females completed a dual n-back working memory task with two target inputs of color and location stimuli in three difficulty levels (n = 0, 1, 2). Functional connectivity matrices were extracted for each subject for each memory load level. Females made less errors than males while spending more time performing the task for all workload levels except in 0-back related to the color stimulus, where the reaction time of females was shorter than males. The results of functional connectivity reveal the inverse behavior of two hemispheres at different memory workload levels between males and females. In the left hemisphere, males exhibited stronger connectivity compared to the females, while stronger connectivity was observed in the females' right hemisphere. Furthermore, an inverse trend was detected in the channel pairs with significant connectivity in the right hemisphere of males (falling) and females (rising) by enhancing working memory load level. Considering both behavioral and functional results for two sexes demonstrated a better performance in females due to the more effective use of the brain. The results indicate that sex affects functional connectivity between different areas in both hemispheres of the brain during cognitive tasks of varying difficulty levels although the general impression is that spatial capabilities are considered as a performance of the brain's right hemisphere. These results reinforce the presence of a sex effect in the functional imaging studies of hemodynamic function and emphasize the importance of evaluating brain network connectivity for achieving a better scientific understanding of sex differences.

597 - Examining the relationship between brain network connectivity and cognitive attention following acquired brain injury: a systematic review of structual and functional measures

597 - Examining the relationship between brain network connectivity and cognitive attention following acquired brain injury: a systematic review of structual and functional measures

Evaluating the depression state during perinatal period by non-invasive scalp EEG.

Perinatal depression, with a prevalence of 10 to 20% in United States, is usually missed as multiple symptoms of perinatal depression are common in pregnant women. Worse, the diagnosis of perinatal depression still largely relies on questionnaires, leaving the objective biomarker being unveiled yet. This study suggested a safe and non-invasive technique to diagnose perinatal depression and further explore its underlying mechanism. Considering the non-invasiveness and clinical convenience of electroencephalogram for mothers-to-be and fetuses, we collected the resting-state electroencephalogram of pregnant women at the 38th week of gestation. Subsequently, the difference in network topology between perinatal depression patients and healthy mothers-to-be was explored, with related spatial patterns being adopted to achieve the classification of pregnant women with perinatal depression from those healthy ones. We found that the perinatal depression patients had decreased brain network connectivity, which indexed impaired efficiency of information processing. By adopting the spatial patterns, the perinatal depression could be accurately recognized with an accuracy of 87.88%; meanwhile, the depression severity at the individual level was effectively predicted, as well. These findings consistently illustrated that the resting-state electroencephalogram network could be a reliable tool for investigating the depression state across pregnant women, and will further facilitate the clinical diagnosis of perinatal depression.

Higher-Order Intrinsic Brain Network Trajectories After Antipsychotic Treatment in Medication-Naïve Patients With First-Episode Psychosis

BackgroundIntrinsic brain network connectivity is already altered in first-episode psychosis (FEP), but the longitudinal trajectories of network connectivity, especially in response to antipsychotic treatment, remain poorly understood. The goal of this study was to investigate how antipsychotic medications affect higher-order intrinsic brain network connectivity in FEP. MethodsData from 87 antipsychotic medication-naïve patients with FEP and 87 healthy control participants were used. Medication-naïve patients received antipsychotic treatment for 16 weeks. Resting-state functional connectivity (FC) of the default mode, salience, dorsal attention, and executive control networks were assessed prior to treatment and at 6 and 16 weeks after treatment. We evaluated baseline and FC changes using linear mixed models to test group × time interactions within each network. Associations between FC changes after 16 weeks and response to treatment were also evaluated. ResultsPrior to treatment, significant group differences in all networks were found. However, significant trajectory changes in FC were found only in the default mode and executive control networks. Changes in FC in these networks were associated with treatment response. Several sensitivity analyses showed a consistent normalization of executive control network FC in response to antipsychotic treatment. ConclusionsHere, we found that alterations in intrinsic brain network FC were not only alleviated with antipsychotic treatment, but the extent of this normalization was also associated with the degree of reduction in symptom severity. Taken together, our data suggest modulation of intrinsic brain network connectivity (mainly frontoparietal connectivity) as a mechanism underlying antipsychotic treatment response in FEP.

Language First, Cognition Later: Different Trajectories of Subcomponents of the Future-Reading Network in Processing Narratives from Kindergarten to Adolescence.

Narrative comprehension is a linguistic ability that emerges early in life and has a critical role in language development, reading acquisition, and comprehension. According to the Simple View of Reading model, reading is acquired through word decoding and linguistic comprehension. Here, within and between networks, functional connectivity in several brain networks supporting both language and reading abilities was examined from prereading to proficient reading age in 32 healthy children, ages 5-18 years, scanned annually while listening to stories over 12 years. Functional connectivity changes within and between the networks were assessed and compared between the years using hierarchical linear regression and were related to reading abilities. At prereading age, the networks related to basic language processing accounted for 32.5% of the variation of reading ability at reading age (at 12-14 years) (R2 = 0.325, p = 0.05). At age 17, more complex cognitive networks were involved and accounted for 97.4% of the variation in reading ability (R2 = 0.974, p = 0.022). Overall, networks composing the future-reading network are highly involved in processing narratives along development; however, networks related to semantic, phonological, and syntactic processing predict reading ability earlier in life, and more complex networks predict reading proficiency later in life.