Resting State Neural Networks Research Articles

Нейровизуализационный подход для выявления биомаркеров рабочей памяти у больных с хронической ишемией мозга

Verbal working memory (VWM) is a fundamental function responsible for temporary storage and short-term handling of verbal information. The study was aimed to determine the working memory biomarker associated with imaging of the source of infra-slow electrical activity in patients with chronic cerebral ischemia (CCI). A total of 50 patients with CCI took part in the study: 16 males and 34 females aged 50–85 years. VWM was evaluated by the Luria test. The subjects were divided into two groups matched by age with the VWM below and above the average level for the studied sample. The infra-slow, below 0.1 Hz, electrical activity, otherwise known as the DC potentials (DCPs) of the brain, was recorded with five monopolar leads: frontal, central, occipital, right and left temporal. The resting state fMRI was used to analyze brain regions with the activated BOLD (blood-oxygen-level-dependent) signal that were associated with the brain regions responsible for VWM and the DCP generation sources recorded with the non-polarizable electrodes. The differences in BOLD signal activation and infra-slow activity amplitude were found in two VWM groups. These resting-state neural networks, VWM and the neural network responsible for DCP generation, overlapped in frontal regions. There were significant differences in DCP recorded with the frontal lead in two VWM groups (р = 0.00004). In patients with CCI, infra-slow activity, recorded with the frontal lead that is generated by the neural network fragment representing an intersection of the VWM network and the part of the brain responsible for DCP generation in the frontal region, is a VWM biomarker.

Vitamin B6, B12, and Folate's Influence on Neural Networks in the UK Biobank Cohort.

One-carbon metabolism coenzymes may influence brain aging in cognitively unimpaired adults. Baseline data were used from the UK Biobank cohort. Estimated intake of vitamin B6, B12, and folate was regressed onto neural network functional connectivity in five resting-state neural networks. Linear mixed models tested coenzyme main effects and interactions with Alzheimer's disease (AD) risk factors. Increased B6 and B12 estimated intake were linked with less functional connectivity in most networks, including the posterior portion of the Default Mode Network. Conversely, higher folate was related to more connectivity in similar networks. AD family history modulated these associations: Increased estimated intake was positively associated with stronger connectivity in the Primary Visual Network and Posterior Default Mode Network in participants with an AD family history. In contrast, increased vitamin B12 estimated intake was associated with less connectivity in the Primary Visual Network and the Cerebello-Thalamo-Cortical Network in those without an AD family history. The differential patterns of association between B vitamins and resting-state brain activity may be important in understanding AD-related changes in the brain. Notably, AD family history appears to play a key role in modulating these relationships.

Abnormal functional connectivity in radiologically isolated syndrome: A resting-state fMRI study

Background: Radiologically isolated syndrome (RIS) patients might have psychiatric and cognitive deficits, which suggests an involvement of major resting-state functional networks. Notwithstanding, very little is known about the neural networks involved in RIS. Objective: To examine functional connectivity differences between RIS and healthy controls using resting-state functional magnetic resonance imaging (fMRI). Methods: Resting-state fMRI data in 25 RIS patients and 28 healthy controls were analyzed using an independent component analysis; in addition, seed-based correlation analysis was used to obtain more information about specific differences in the functional connectivity of resting-state networks. Participants also underwent neuropsychological testing. Results: RIS patients did not differ from the healthy controls regarding age, sex, and years of education. However, in memory (verbal and visuospatial) and executive functions, RIS patients’ cognitive performance was significantly worse than the healthy controls. In addition, fluid intelligence was also affected. Twelve out of 25 (48%) RIS patients failed at least one cognitive test, and six (24.0%) had cognitive impairment. Compared to healthy controls, RIS patients showed higher functional connectivity between the default mode network and the right middle and superior frontal gyri and between the central executive network and the right thalamus (pFDR < 0.05; corrected). In addition, the seed-based correlation analysis revealed that RIS patients presented higher functional connectivity between the posterior cingulate cortex, an important hub in neural networks, and the right precuneus. Conclusion: RIS patients had abnormal brain connectivity in major resting-state neural networks and worse performance in neurocognitive tests. This entity should be considered not an “incidental finding” but an exclusively non-motor (neurocognitive) variant of multiple sclerosis.

Effects of Alterations in Resting-State Neural Networks on the Severity of Neuropathic Pain after Spinal Cord Injury.

Neuropathic pain (NP) following spinal cord injury (SCI) is refractory to pain control strategies, and the underlying neuronal mechanisms remain poorly understood. This study aimed to determine the brain regions engaged in maintaining a spontaneous resting state and the link between those regions and the severity of NP in patients with incomplete SCI. Seventy-three subjects (41 patients and 32 age- and sex-matched healthy controls) participated in this retrospective study. Regarding the neurological level of injury, patients with incomplete SCI experienced at-level or below-level NP. The severity of NP was evaluated using a visual analog scale (VAS), and patients were divided into mild and moderate-severe NP groups based on VAS scores. Graph theory and fractional amplitude of low-frequency fluctuation (fALFF) analyses were performed to compare resting-state functional magnetic resonance imaging (fMRI) analysis results among the three groups. Graph theory analysis was performed through a region of interest (ROI)-to-ROI analysis and then fALFF analysis was performed in the brain regions demonstrating significant differences among the three groups analyzed using the graph theory. We evaluated whether the brain regions showing significant differences using graph theory and fALFF correlated with the VAS scores. Patients with moderate-severe NP showed reduced node degree and fALFF in the left middle frontal gyrus compared with those with mild NP and healthy controls. Furthermore, patients with severe NP demonstrated increased average path lengths and reduced fALFF values in the posterior cingulate gyrus. This study found that changes in intrinsic oscillations of fMRI signals in the middle frontal gyrus and posterior cingulate gyrus were significant considering the severity of NP.

5-HT4 Receptor Agonist Effects on Functional Connectivity in the Human Brain: Implications for Procognitive Action

BackgroundCognitive deficits are often comorbid with mood disorders and can cause significant functional impairment even after resolution of the primary mood symptoms. We do not currently have pharmacological treatments that adequately address these deficits. 5-HT4 receptor agonists show promise as potential procognitive agents in animal and early human translational studies. Optimal cognitive performance in humans is directly associated with appropriate functional connectivity between specific resting-state neural networks. However, so far the effect of 5-HT4 receptor agonism on resting-state functional connectivity (rsFC) in the brain in humans is unknown. MethodsWe collected resting-state functional magnetic resonance imaging scans from 50 healthy volunteers, of whom 25 received 6 days × 1 mg prucalopride (a highly selective 5-HT4 receptor agonist) and 25 received placebo in a randomized double-blind design. ResultsNetwork analyses identified that participants in the prucalopride group had enhanced rsFC between the central executive network and the posterior/anterior cingulate cortex. Seed analyses also showed greater rsFC between the left and right rostral anterior cingulate cortex and the left lateral occipital cortex, and reduced rsFC between the hippocampus and other default mode network regions. ConclusionsSimilar to other potentially procognitive medications, low-dose prucalopride in healthy volunteers appeared to enhance rsFC between regions involved in cognitive networks and reduce rsFC within the default mode network. This suggests a mechanism for the behavioral cognitive enhancement previously seen with 5-HT4 receptor agonists in humans and supports the potential for 5-HT4 receptor agonists to be used in clinical psychiatric populations.

Treatment response with ketamine in chronic suicidality: An open label functional connectivity study

BackgroundKetamine has recently been proposed as a treatment option for suicidality. Whilst its mechanism of action has been explored at molecular levels, the effect on the brain at the organ level remains unclear. Here we investigate immediate post-treatment and prolonged large-scale resting-state neural network changes to elucidate the neuronal underpinnings associated with ketamine's therapeutic effects. MethodsTwenty-eight adults (aged 22–72 years) participated in the Oral Ketamine Trial On Suicidality, which is an open-label trial of weekly sub-anaesthetic doses of oral ketamine over 6 weeks. MRI was acquired at baseline, post-treatment, and follow-up. Functional connectivity changes at post-treatment and follow-up were examined using seed based and independent component analysis. ResultsThe seed-based connectivity analysis revealed significantly reduced connectivity at post-treatment from the right hippocampus to both right and left superior frontal gyrus, from the left anterior parahippocampus to right superior frontal gyrus, left superior frontal gyrus, right middle frontal gyrus, and left frontal operculum cortex. Compared with baseline, the ICA showed reduced anterior default mode network connectivities to bilateral posterior cingulate cortex, middle and anterior cingulate cortex, lingual gyrus, and cuneus and increased connectivity of the frontoparietal network to the right superior parietal lobule at post-treatment. LimitationsOpen label pilot study. ConclusionsWe have shown sub-anaesthetic doses of ketamine alters connectivity in networks which have been shown to be aberrantly hyper-connected in numerous psychiatric conditions. These neurocircuitry changes are supported by significant reductions in suicide ideation. Our results provide support for the use of ketamine as a treatment for suicidality.

The modulatory effect of adaptive task-switching training on resting-state neural network dynamics in younger and older adults

With increasing life expectancy and active aging, it becomes crucial to investigate methods which could compensate for generally detected cognitive aging processes. A promising candidate is adaptive cognitive training, during which task difficulty is adjusted to the participants’ performance level to enhance the training and potential transfer effects. Measuring intrinsic brain activity is suitable for detecting possible distributed training-effects since resting-state dynamics are linked to the brain’s functional flexibility and the effectiveness of different cognitive processes. Therefore, we investigated if adaptive task-switching training could modulate resting-state neural dynamics in younger (18–25 years) and older (60–75 years) adults (79 people altogether). We examined spectral power density on resting-state EEG data for measuring oscillatory activity, and multiscale entropy for detecting intrinsic neural complexity. Decreased coarse timescale entropy and lower frequency band power as well as increased fine timescale entropy and higher frequency band power revealed a shift from more global to local information processing with aging before training. However, cognitive training modulated these age-group differences, as coarse timescale entropy and lower frequency band power increased from pre- to post-training in the old-training group. Overall, our results suggest that cognitive training can modulate neural dynamics even when measured outside of the trained task.

Regional Neural Activity Abnormalities and Whole-Brain Functional Connectivity Reorganization in Bulimia Nervosa: Evidence From Resting-State fMRI.

The management of eating behavior in bulimia nervosa (BN) patients is a complex process, and BN involves activity in multiple brain regions that integrate internal and external functional information. This functional information integration occurs in brain regions involved in reward, cognition, attention, memory, emotion, smell, taste, vision and so on. Although it has been reported that resting-state brain activity in BN patients is different from that of healthy controls, the neural mechanisms remain unclear and need to be further explored. The fractional amplitude of low-frequency fluctuation (fALFF) analyses are an important data-driven method that can measure the relative contribution of low-frequency fluctuations within a specific frequency band to the whole detectable frequency range. The fALFF is well suited to reveal the strength of interregional cooperation at the single-voxel level to investigate local neuronal activity power. FC is a brain network analysis method based on the level of correlated dynamics between time series, which establishes the connection between two spatial regions of interest (ROIs) with the assistance of linear temporal correlation. Based on the psychological characteristics of patients with BN and the abnormal brain functional activities revealed by previous neuroimaging studies, in this study, we investigated alterations in regional neural activity by applying fALFF analysis and whole-brain functional connectivity (FC) in patients with BN in the resting state and to explore correlations between brain activities and eating behavior. We found that the left insula and bilateral inferior parietal lobule (IPL), as key nodes in the reorganized resting-state neural network, had altered FC with other brain regions associated with reward, emotion, cognition, memory, smell/taste, and vision-related functional processing, which may have influenced restrained eating behavior. These results could provide a further theoretical basis and potential effective targets for neuropsychological treatment in patients with BN.

The Resting-State Neural Network of Delay Discounting.

Delay discounting is a common phenomenon in daily life, which refers to the subjective value of a future reward decreasing as a function of time. Previous studies have identified several cortical regions involved in delay discounting, but the neural network constructed by the cortical regions of delay discounting is less clear. In this study, we employed resting-state functional magnetic resonance imaging (RS-fMRI) to measure the spontaneous neural activity in a large sample of healthy young adults and used the Monetary Choice Questionnaire to directly measure participants’ level of delay discounting. To identify the neural network of delay discounting at rest, we used an individual difference approach to explore brain regions whose spontaneous activities were related to delay discounting across the whole brain. Then, these brain regions served as seeds to identify the neural network of delay discounting. We found that the fractional amplitude of low-frequency fluctuations (fALFF) of the left insula were positively correlated to delay discounting. More importantly, its connectivity to the anterior cingulate cortex was read out for participants’ behavioral performance in the task of delay discounting. In short, our study provides empirical evidence that insula-anterior cingulate cortex connectivity may serve as a part of the neural network for delay discounting.

Altered resting-state neural networks in children and adolescents with functional neurological disorder

ObjectivesPrevious studies with adults suggest that aberrant communication between neural networks underpins functional neurological disorder (FND). The current study adopts a data-driven approach to investigate the extent that functional resting-state networks are disrupted in a pediatric mixed-FND cohort. Methods31 children with mixed FND and 33 age- and sex-matched healthy controls completed resting-state fMRI scans. Whole-brain independent component analysis (pFWE < 0.05) was then used to identify group differences in resting-state connectivity. Self-report measures included the Depression, Anxiety and Stress Scale (DASS-21) and Early Life Stress Questionnaire (ELSQ). Resting-state heart rate (HR) and cortisol-awakening response (CAR) were available in a subset. ResultsChildren with FND showed wide-ranging connectivity changes in eight independent components corresponding to eight resting-state neural networks: language networks (IC6 and IC1), visual network, frontoparietal network, salience network, dorsal attention network, cerebellar network, and sensorimotor network. Children whose clinical presentation included functional seizures (vs children with other FND symptoms) showed greater connectivity decreases in the frontoparietal and dorsal attentional networks. Subjective distress (total DASS score), autonomic arousal (indexed by HR), and HPA dysregulation (attenuated/reversed CAR) contributed to changes in neural network connectivity. Children with FND (vs controls) reported more subjective distress (total DASS score) and more adverse childhood experiences (ACEs) across their lifespan. ConclusionsChildren with FND demonstrate changes in resting-state connectivity. Identified network alterations underpin a broad range of functions typically disrupted in children with FND. This study complements the adult literature by suggesting that FND in children and adolescents emerges in the context of their lived experience and that it reflects aberrant communication across neural networks.

Resting-state neural networks in cognitive decline in patients with vascular encephalopathy

We evaluated the connectivity reorganization of resting-state neural networks in patients with cognitive decline secondary to vascular encephalopathy (VE). Quantitative cognitive functions were evaluated using the Montreal Cognitive Assessment (MoCA) scale and compared with the organization of resting-state neural networks recorded using functional magnetic resonance imaging (fMRI). The aim of this work was to assess the relationship between various resting-state neural networks and cognitive function. Materials and methods. The study involved 29 people with VE, divided into two groups: without cognitive decline (≥ 26 points on the MoCA) and with cognitive impairment (24–18 points on the MoCA). Connectivity between different brain regions was evaluated in all patients using resting-state fMRI, with SPM-12 and CONN18b software applications in Matlab. Results and conclusion. Statistically significant differences in connectivity were found between groups in the dorsal attention network, visual network, and sensorimotor networks, as well as in the left parahippocampal cortex. New, negative connectivity was observed alongside cognitive decline, which, together with reduced connectivity in resting-state neural networks, can be considered an obligatory sign accompanying cognitive impairment in VE.

Altered Granger Causal Connectivity of Resting-State Neural Networks in Patients With Leukoaraiosis-Associated Cognitive Impairment-A Cross-Sectional Study.

Background: The purpose of this study was to provide an imaging reference for the measurement of disease progression, as well as to reveal the pathogenesis of leukoaraiosis (LA).Methods: Eighty-seven subjects were divided into three groups: LA patients with vascular dementia (LA-VaD) (20 subjects: 14 female, 6 male), LA patients with vascular cognitive impairment nondementia (LA-VCIND) (32 subjects: 14 male, 18 female), and normal controls (NC) (35 subjects: 14 male, 21 female). A multivariate Granger causality analysis (mGCA) was applied to the resting-state networks (RSNs) to evaluate the possible effective connectivity within the resting-state networks retrieved by independent component analysis (ICA) from resting-state functional magnetic resonance imaging (rs-fMRI) data.Results: Ten RSNs were identified: the primary visual network, secondary visual network, auditory network, sensorimotor network, anterior default mode network, posterior default mode network, salience network, dorsal attention network, left working memory network, and the right working memory network. Using independent component analysis, significant average Z scores were found in the anterior default mode network, salience network, dorsal attention network, and right working memory network between LA-VAD and NC groups. The functional connectivity (FC) strength of the networks was different between the NC, LA-VCIND, and LA-VaD groups. Effective connectivity between RSNs was compensated by either increased or decreased effective connectivity changes in these three groups.Conclusions: The components of resting-state networks kept changing as the disease progressed. Meanwhile, the activation intensity increased at the early stage of LA and decreased as patients' cognitive impairment aggravated. Furthermore, the direction and strength of connections between these networks changed and remodeled differently. These suggest that the human brain compensates for specific functional changes at different stages.

The neural basis of executive functioning deficits in adolescents with epilepsy: a resting-state fMRI connectivity study of working memory.

Working memory deficits are common in youth with epilepsy and consistently associated with long-term negative outcomes. Existing research on the neural basis of working memory disruptions in pediatric epilepsy is limited. The question of whether differences in the functional connectivity of neural networks underlie working memory disruptions in pediatric patients with epilepsy remains unanswered. A total of 49 adolescents between the ages of 13-17years participated in this study. Twenty-nine adolescents had confirmed epilepsy (n = 17 generalized epilepsy, n = 6 localization-related, n = 6 unclassified). The control group included 20 healthy adolescents. A total of 10-min resting state functional magnetic resonance imaging was obtained for all participants. NeuroSynth-derived regions of interest were used as nodes that comprise working memory neural networks. Group differences in resting state functional connectivity were examined between adolescents with epilepsy and controls. Functional connectivity was computed as the temporal correlation of functional magnetic resonance imaging signal fluctuations between any two regions of interest. Compared to controls, adolescents in the epilepsy group demonstrated both hypoconnectivity and hyperconnectivity in cortical areas that map onto fronto-parietal and cingulo-opercular networks, as well as cerebellar regions. Functional connectivity between pairs of regions of interest was also significantly associated with behavioral measures of working memory across epilepsy and control groups. This study demonstrates that the presence of abnormal patterns in resting state neural network connectivity may underlie the working memory disruptions that frequently characterize the neurocognitive profile of youth with epilepsy.

Emotion dysregulation and mechanisms in attention deficit hyperactivity disorder

Attention deficit hyperactivity disorder (ADHD) is a kind of mental development disorder with high prevalence. Its core symptoms are attention deficit, hyperactivity and impulse.Previous studies mainly focused on the executive function and cognitive control of ADHD. Since emotion dysregulation in ADHD results in a lot of negative consequences, such as social interaction, coping with frustration and parent-child relationship, more and more researchers believe that the lack of emotional regulation ability is likely to be an important reason for ADHD patients' inability to focus attention and hyperactive impulse behavior in recent years.At the behavioral level, ADHD patients' emotion dysregulation is mainly reflected in emotional impulsivity, emotional lability and negative emotionality.At the neurophysiological level, emotion dysregulation in ADHD patients was found to be related to heart rate variability, respiratory sinus arrhythmia, late positive component LPP and activity abnormality of resting state neural network. Some researchers have proposed the cold and hot executive function theory of ADHD, in which the hot regulatory circuit is associated with the processing the emotional regulation process. Future studies are needed to explore the maintaining difficulty and inducing positive emotion in ADHD, and the influence of comorbidities in ADHD. Moreover, researchers should combine neurophysiological method and family study to clarify the brain mechanism and its genetic basis underlying emotion dysregulation in ADHD patients. Key words: Attention deficit hyperactivity disorder; Emotion regulation; Impulsivity; Inhibition; Brain mechanism

Age-related Trends in Functional Organization of Cortical Parts of Regulatory Brain Systems in Adolescents: an Analysis of Resting-State Networks in the EEG Source Space

Age-related trends in the strength of functional and effective connectivity between key cortical structures that belong to the three most important resting-state neural networks: the default mode network (DMN), the key event detection network (salience network, SN) and the central executive network (CEN) were investigated in adolescents of both sexes. The study involved 34 adolescents of the younger age group: 11–13 years old (12.61 ± 0.75 years, 13 girls and 21 boys) and 54 adolescents of the older group: 14–16 years old (15.00 ± 0.75 years, 20 girls and 34 boys). Frequency-specific estimates of the strength of functional and effective connectivity between the nodes of DMN, SN and CEN were computed in six frequency bands θ (4–7 Hz), α1 (7.5–9.5 Hz), α2 (10–13 Hz), β1 (14–18 Hz), β2 (20–27 Hz) and γ (30–40 Hz) using the vector autoregressive modeling of cortical sources of EEG registered in the resting condition. The analysis of functional connectivity revealed age differences in the θ frequency range, in which the strength of connections between the nodes of all networks in the younger age group was higher than in the older group. Besides, sex-related differences were found in the beta-2 and gamma ranges: the connections between the nodes of DMN were stronger for girls than for boys. The analysis of effective connectivity (directed influences) revealed a significant effect of age in all frequency ranges for the CEN and DMN resting-state networks; for SN, this effect was significant in all but the beta-2 and gamma ranges. The most pronounced age-related changes were found for bottom-up connections directed from more caudal to more frontal areas in CEN and DMN, and in the younger age group, the strength of effective connections was greater than in the older one. The effect of sex on the strength of effective connections was limited mainly to the younger group and manifested itself in stronger DMN and CEN connectivity in girls (as compared with boys) .

Resting-state neural network disturbances that underpin the emergence of emotional symptoms in adolescent girls: resting-state fMRI study.

Subsyndromal emotional symptoms in adolescence may represent precursors for full-blown emotional disorders in early adulthood. Understanding the neurobiological mechanisms that drive this development is essential for prevention. Self-referential processing and emotion regulation are remodelled substantively during adolescence, therefore this study examined integration of key neural networks involved in these processes. At baseline, clinical and resting-state functional magnetic resonance imaging data were collected for 88 adolescent girls (mean age 15 years), and 71 of these girls underwent repeat clinical assessment after 2 years. These 71 girls were then partitioned into two groups depending on the presence (ES+) or absence (ES-) of emotional symptoms, and differences in dynamic functional network connectivity were determined and correlated with clinical variables. The two groups displayed a differential pattern of functional connectivity involving the left lateral prefrontal network (LPFN). Specifically, in the ES+ group this network displayed positive coupling with the right LPFN but negative coupling with the default mode network, and the inverse of this pattern was found in the ES- group. Furthermore, the coupling strengths between left and right LPFN at the irst time point predicted follow-up depression and state anxiety scores. Our findings suggest that in adolescent girls, emotional symptoms may emerge as a result of impaired integration between networks involved in self-referential information processing and approach-avoidance behaviours. These impairments can compromise the pursuit of important goals and have an impact on emotion processing and finally may lead to the development of emotional disorders, such as anxiety and depression in adulthood. None.

The Impact of Caregiving on the Association Between Infant Emotional Behavior and Resting State Neural Network Functional Topology.

The extent to which neural networks underlying emotional behavior in infancy serve as precursors of later behavioral and emotional problems is unclear. Even less is known about caregiving influences on these early brain-behavior relationships. To study brain-emotional behavior relationships in infants, we examined resting-state functional network metrics and infant emotional behavior in the context of early maternal caregiving. We assessed 46 3-month-old infants and their mothers from a community sample. Infants underwent functional MRI during sleep. Resting-state data were processed using graph theory techniques to examine specific nodal metrics as indicators of network functionality. Infant positive and negative emotional behaviors, and positive, negative and mental-state talk (MST) indices of maternal caregiving were coded independently from filmed interactions. Regression analyses tested associations among nodal metrics and infant emotionality, and the moderating effects of maternal behavior on these relationships. All results were FDR corrected at alpha = 0.05. While relationships between infant emotional behavior or maternal caregiving, and nodal metrics were weak, higher levels of maternal MST strengthened associations between infant positive emotionality and nodal metrics within prefrontal (p < 0.0001), and occipital (p < 0.0001) cortices more generally. Positive and negative aspects of maternal caregiving had little effect. Our findings suggest that maternal MST may play an important role in strengthening links between emotion regulation neural circuitry and early infant positive behavior. They also provide objective neural markers that could inform and monitor caregiving-based interventions designed to improve the health and well-being of vulnerable infants at-risk for behavioral and emotional problems.

Exposure-based therapy changes amygdala and hippocampus resting-state functional connectivity in patients with posttraumatic stress disorder.

Recent research suggests that posttraumatic stress disorder (PTSD) is associated with altered amygdala and hippocampal resting-state functional connectivity (rsFC). However, less research has examined whether Prolonged Exposure (PE), a first line exposure-based treatment for PTSD, has the potential to alter resting state neural networks. A total of 24 patients with PTSD and 26 matched trauma-exposed healthy controls (TEHCs) underwent resting-state functional magnetic resonance imaging (fMRI) at baseline. PTSD patients were scanned a second time after completing 10-session PE in which patients narrated a detailed trauma account (imaginal exposure) and confronted trauma reminders (in vivo exposure) to extinguish trauma-related fear responses. TEHC were scanned again following a 10-week waiting period. Seed regions of interest (ROIs) included centromedial amygdala (CMA), basolateral amygdala (BLA), and the hippocampus. Post- versus pretreatment comparisons indicated increased rsFC of the BLA and CMA with the orbitofrontal cortex (OFC), and hippocampus-medial prefrontal cortex (mPFC) among patients with PTSD, but not among TEHC participants. Enhanced amygdala and hippocampus rsFC with prefrontal cortical regions following PE could underlie improved capacity for inhibition and re-evaluation of threat, and heightened memory encoding and retrieval ability, respectively. These findings encourage further investigation of this circuitry as a therapeutic target in PTSD.

Effects of High BMI on Synaptic Function and Metabolic Connectivity in the Brain—Evidence of Gender Difference

Several studies reported a significant association with obesity and cognitive deficits in aging, especially for executive, attention and memory domains. The neural effects of obesity and the correlated cognitive dysfunction have yet to be elucidated. We retrospectively collected a large cohort of healthy elderlies (N=222; age=74.03±5.88y; M/F=112/105; BMI range=19.21-38.79), from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. All subjects underwent in vivo positron emission tomography with 18F-Fluorodeoxyglucose (FDG), thus we were able to evaluate the correlation between BMI, synaptic function and metabolic connectivity in the whole brain and within the resting-state neural networks, crucially considering the effect of gender. We found a significant positive correlation between BMI levels and brain metabolism in female group only (R=.435; P&amp;lt;0.001), with high BMI associated with increased glucose consumption in the orbitofrontal cortex. Whole brain connectivity analysis revealed an altered pattern in frontal regions in females with high BMI, namely a decreased connectivity between orbitofrontal regions and high-order prefrontal cortex, and an abnormally elevated connectivity with nucleus accumbens. The connectivity analysis of the resting-state brain networks confirmed that in elderly females with high BMI, the core of vulnerability is within the frontal regions, with impaired connectivity in executive and salience networks. In contrast, elderly males with high BMI showed loss of long-distance connections between frontal and parietal cortices, invariantly across attentional, executive and posterior default mode networks. Our findings support a strong detrimental effect of high BMI levels on brain metabolism and neural connectivity in healthy aging, with gender differences. Notably, high BMI in females affects the executive and reward systems. This evidence brings to considerations for medical practice and health policy. Disclosure A. Sala: None. M. Malpetti: None. A. Ferrulli: None. L. Gianolli: None. L. Luzi: Speaker's Bureau; Self; A. Menarini Diagnostics, AstraZeneca, Eli Lilly and Company. Research Support; Self; Gelesis. Consultant; Self; McKinsey &amp; Company. Speaker's Bureau; Self; Menarini Group, Merck Sharp &amp; Dohme Corp.. Research Support; Self; Novartis AG. Speaker's Bureau; Self; Novo Nordisk A/S. Research Support; Self; Sunstar Foundation. Speaker's Bureau; Self; Smith &amp; Nephew. D. Perani: None.

Corticostriatal Connectivity in Antisocial Personality Disorder by MAO-A Genotype and Its Relationship to Aggressive Behavior.

BackgroundThe influence of genetic variation on resting-state neural networks represents a burgeoning line of inquiry in psychiatric research. Monoamine oxidase A, an X-linked gene, is one example of a molecular target linked to brain activity in psychiatric illness. Monoamine oxidase A genetic variants, including the high and low variable nucleotide tandem repeat polymorphisms, have been shown to differentially affect brain functional connectivity in healthy humans. However, it is currently unknown whether these same polymorphisms influence resting-state brain activity in clinical conditions. Given its high burden on society and strong connection to violent behavior, antisocial personality disorder is a logical condition to study, since in vivo markers of monoamine oxidase A brain enzyme are reduced in key affect-modulating regions, and striatal levels of monoamine oxidase A show a relation with the functional connectivity of this same region.MethodsWe utilized monoamine oxidase A genotyping and seed-to-voxel-based functional connectivity to investigate the relationship between genotype and corticostriatal connectivity in 21 male participants with severe antisocial personality disorder and 19 male healthy controls.ResultsDorsal striatal connectivity to the frontal pole and anterior cingulate gyrus differentiated antisocial personality disorder subjects and healthy controls by monoamine oxidase A genotype. Furthermore, the linear relationship of proactive aggression to superior ventral striatal-angular gyrus functional connectivity differed by monoamine oxidase A genotype in the antisocial personality disorder groups.ConclusionsThese results suggest that monoamine oxidase A genotype may affect corticostriatal connectivity in antisocial personality disorder and that these functional connections may also underlie use of proactive aggression in a genotype-specific manner.