Resting-state Function Research Articles

Brain Entropy Study on Obsessive-Compulsive Disorder Using Resting-State fMRI.

Object: Brain entropy is a potential index in the diagnosis of mental diseases, but there are some differences in different brain entropy calculation, which may bring confusion and difficulties to the application of brain entropy. Based on the resting-state function magnetic resonance imaging (fMRI) we analyzed the differences of the three main brain entropy in the statistical significance, including approximate entropy (ApEn), sample entropy (SampEn) and fuzzy entropy (FuzzyEn), and studied the physiological reasons behind the difference through comparing their performance on obsessive-compulsive disorder (OCD) and the healthy control (HC).Method: We set patients with OCD as the experimental group and healthy subjects as the control group. The brain entropy of the OCD group and the HC are calculated, respectively, by voxel and AAL region. And then we analyzed the statistical differences of the three brain entropies between the patients and the control group. To compare the sensitivity and robustness of these three kinds of entropy, we also studied their performance by using certain signal mixed with noise.Result: Compare with the control group, almost the whole brain's ApEn and FuzzyEn of OCD are larger significantly. Besides, there are more brain regions with obvious differences when using ApEn comparing to using FuzzyEn. There was no statistical difference between the SampEn of OCD and HC.Conclusion: Brain entropy is a numerical index related to brain function and can be used as a supplementary biological index to evaluate brain state, which may be used as a reference for the diagnosis of mental illness. According to an analysis of certain signal mixed with noise, we conclude that FuzzyEn is more accurate considering sensitivity, stability and robustness of entropy.

Near-infrared spectroscopy as a promising tool in stroke: Current applications and future perspectives

Stroke is caused by an acute focal disruption of the vasculature in the central nervous system. Neurological-related functional deficits are the most devastating consequences for stroke survivors. Neural signals from stroke patients can reflect the functional statuses of patients and provide insights into the neuronal recovery mechanism for functioning, which could be used as the basis for designing optimal treatment strategies. Near-infrared spectroscopy (NIRS) is a low-cost, noninvasive, easily operated neuroimage method and it is compatible with various rehabilitative programs. These advantages make NIRS an excellent candidate in research for stroke recovery. Here, we focused on the brain functions and recovery for stroke patients at stable status, conducted a systematic literature review about NIRS applications in stroke since 2000 and identified a total of 72 references through ScienceDirect and PubMed database retrieval. The NIRS studies in stroke include resting-state function and its recovery, motor function and its recovery, motor and cognition interference, cognitive function and its recovery, language function and its recovery, emotional function and its recovery and other applications. Based on the results of the quality assessment, we identified some study gaps from the previous research and provided suggestions for some methodological improvement in the future. The trend of NIRS gives a boost to its application in stroke, and the potential research directions for NIRS in stroke are prospected, including multi-center clinical research, treatment efficacy prediction research and brain–muscle coupling research. Finally, limitations of NIRS are discussed.

Altered brain activity mediates the relationship between white matter hyperintensity severity and cognition in older adults.

White matter hyperintensities (WMHs) on magnetic resonance imaging are commonly found in older adults. The mechanisms underpinning the dose-dependent association between WMH severity and cognition are not well understood. This study aimed to investigate how brain activity changes with WMH severity, and if altered brain activity mediates the relationship between WMH and cognitive function. A total of 35 participants with moderate to severe WMHs (Fazekas grade 2 or 3) and 34 participants with mild WMHs (Fazekas grade 1), who were cognitively normal, were included. Resting-state brain function was analyzed using the amplitude of low-frequency fluctuation (ALFF). A mean fractional anisotropy (FA) value of 20 tract-specific regions of interest was calculated. Mediation analysis was used to assess whether ALFF values mediated the relationship between WMH and cognition. The results showed that compared to those with mild WMHs, participants with confluent WMHs had worse memory and naming ability and also had increased ALFF in the right middle frontal gyrus and decreased ALFF in the left middle occipital gyrus. After controlling for age, gender, education and apolipoprotein E (ApoE) ε4 status, increased ALFF in the right prefrontal cortex was associated with worse immediate recall and recognition, and ALFF values mediated the relationships between both Fazekas scores and FA values and memory. In conclusion, our study suggests that cognitively normal adults with high WMH load exhibit subclinical cognitive dysfunction and altered spontaneous brain activity. The mediating effects of brain activity help to shed light on our understanding of the relationship between WMHs and cognition.

Diagnostic Efficacy of Voxel-Mirrored Homotopic Connectivity in Vascular Dementia as Compared to Alzheimer's Related Neurodegenerative Diseases-A Resting State fMRI Study.

Previous studies have demonstrated that functional connectivity (FC) of different brain regions in resting state function MRI were abnormal in patients suffering from mild cognitive impairment (MCI) and Alzheimer’s disease (AD) when comparing to healthy controls (HC) using seed based, independent component analysis (ICA) or small world network techniques. A new technique called voxel-mirrored homotopic connectivity (VMHC) was used in the current study to evaluate the value of interhemispheric functional connectivity (IFC) as a diagnostic tool to differentiate vascular dementia (VD) from other Alzheimer’s related neurodegenerative diseases. Eighty-three participants were recruited from the university hospital memory clinic. A multidisciplinary panel formed by a neuroradiologist and two geriatricians classified the participants into VD (13), AD (16), MCI (29), and HC (25) based on clinical history, Montreal Cognitive Assessment Hong Kong version (HK-MoCA) neuropsychological score, structural MRI, MR perfusion, and 18-F Flutametamol (amyloid) PET-CT findings of individual subjects. We adopted the calculation method used by Kelly et al. (2011) and Zuo et al. (2010) in obtaining VMHC maps. Specific patterns of VMHC maps were obtained for VD, AD, and MCI to HC comparison. VD showed significant reduction in VMHC in frontal orbital gyrus and gyrus rectus. Increased VMHC was observed in default mode network (DMN), executive control network (ECN), and the remaining salient network (SN) regions. AD showed a reduction of IFC in all DMN, ECN, and SN regions; whereas MCI showed VMHC reduction in vSN, and increased VMHC in DMN and ECN. When combining VMHC values of relevant brain regions, the accuracy was improved to 87%, 92%, and 83% for VD, AD, and MCI from HC, respectively, in receiver operating characteristic (ROC) analysis. Through studying the VMHC maps and using VMHC values in relevant brain regions, VMHC can be considered as a reliable diagnostic tool for VD, AD, and MCI from HC.

The resting-state cerebro-cerebellar function connectivity and associations with verbal working memory performance

The cerebellum plays an important role in cognitive functions through connecting with the cerebral cortical areas. However, the relationship between the resting-state functional connectivity (FC) pattern of human cerebro-cerebellar circuits and cognition is not fully understood. The present study investigated the FC patterns of human cerebro-cerebellar circuits and their associations with verbal working memory performance (an n-back task with three subtasks: 0-back, 1-back, and 2-back) through resting-state functional magnetic resonance imaging (fMRI) data from 34 healthy subjects. The whole-brain connectivity analysis was used to identify the cortical hubs as regions of interest (ROI). Then ROI-based FC analysis was performed to investigate the connectivity characteristics within the key cortical hubs and their associations with n-back task performance. The results showed that the bilateral cerebellum lobule VI as central hubs had increased FC with the default mode network (DMN) node (e.g., right posterior cingulate cortex) and salient network (SN) node (e.g., right anterior cingulate cortex), while decreased FC with the executive control network (ECN) node (e.g., the bilateral superior frontal gyrus). Furthermore, FC values of the cerebellum lobule VI with DMN and ECN nodes correlated with verbal working memory performance (response time of 2-back task). The results suggest that the cerebro-cerebellar circuits involve the underlying neural basis of verbal working memory processing during the resting state.

Network Analysis of Human Brain Connectivity Reveals Neural Fingerprints of a Compositionality Bias in Signaling Systems.

Compositionality is a hallmark of human language and other symbolic systems: a finite set of meaningful elements can be systematically combined to convey an open-ended array of ideas. Compositionality is not uniformly distributed over expressions in a language or over individuals' communicative behavior: at both levels, variation is observed. Here, we investigate the neural bases of interindividual variability by probing the relationship between intrinsic characteristics of brain networks and compositional behavior. We first collected functional resting-state and diffusion magnetic resonance imaging data from a large participant sample (N = 51). Subsequently, participants took part in two signaling games. They were instructed to learn and reproduce an auditory symbolic system of signals (tone sequences) associated with affective meanings (human faces expressing emotions). Signal-meaning mappings were artificial and had to be learned via repeated signaling interactions. We identified a temporoparietal network in which connection length was related to the degree of compositionality introduced in a signaling system by each player. Graph-theoretic analysis of resting-state functional connectivity revealed that, within that network, compositional behavior was associated with integration measures in 2 semantic hubs: the left posterior cingulate cortex and the left angular gyrus. Our findings link individual variability in compositional biases to variation in the anatomy of semantic networks and in the functional topology of their constituent units.

Electroacupuncture enhances resting-state functional connectivity between dorsal caudate and precuneus and decreases associated leptin levels in overweight/obese subjects.

Electroacupuncture (EA) is a safe and effective method for treating obesity. However, how it modulates reward-related brain activity/functional connectivity and gut hormones remains unclear. We employed resting-state functional magnetic resonance imaging (RS-fMRI) and resting-state functional connectivity (RSFC) to investigate EA induced changes in resting-state activity and RSFC in reward-related regions and its association with gut hormones in overweight/obese subjects who received real (n = 20) and Sham (n = 15) stimulation. Results showed reduced leptin levels was positively correlated with reduced body mass index (BMI) and negatively correlated with increased cognitive-control as measured with Three-Factor-Eating-Questionnaire (TFEQ). Significant time effects on RSFC between dorsal caudate (DC) and precuneus were due to significant increased RSFC strength in both EA and Sham groups. In addition, increased RSFC of DC-precuneus was negatively correlated with reduced BMI and leptin levels in the EA group. Mediation analysis showed that the relationship between increased DC-precuneus RSFC strength and reduced BMI was mediated by reduced leptin levels. These findings reflect the association between EA-induced brain reward-related RSFC and leptin levels, and decreased leptin levels mediated altered DC-precuneus RSFC strength and consequent weight-loss, suggesting the potential role of EA in reducing weight and appetite.

Nicotine acutely alters temporal properties of resting brain states

BackgroundNicotine-dependent individuals have altered activity in neurocognitive networks such as the default mode (DMN), salience (SN) and central executive networks (CEN). One theory suggests that, among chronic tobacco smokers, nicotine abstinence drives more DMN-related internal processing while nicotine replacement suppresses DMN and enhances SN and CEN. Whether acute nicotine impacts network dynamics in non-smokers is, however, unknown. MethodsIn a randomized double-blind crossover study, 17 healthy non-smokers (8 females) were administered placebo and nicotine (2-mg lozenge) on two different days prior to collecting resting-state functional magnetic resonance imaging (fMRI). Previously defined brain states in 462 individuals that spatially overlap with well-characterized resting-state networks including the DMN, SN, and CEN were applied to compute state-specific dynamics at rest: total time spent in state, persistence in each state after entry, and frequency of state transitions. We examined whether nicotine acutely alters these resting-state dynamics. ResultsA significant drug-by-state interaction emerged; post-hoc analyses clarified that, relative to placebo, nicotine suppressed time spent in a frontoinsular-DMN state (posterior cingulate cortex, medial prefrontal cortex, anterior insula, striatum and orbitofrontal cortex) and enhanced time spent in a SN state (anterior cingulate cortex and insula). No significant findings were observed for persistence and frequency. ConclusionsIn non-smokers, nicotine biases resting-state brain function away from the frontoinsular-DMN and toward the SN, which may reduce internally focused cognition and enhance salience processing. While past work suggests nicotine impacts DMN activity, the current work shows nicotinic influences on a specific DMN-like network that has been linked with rumination and depression.

Glutamate and functional connectivity - support for the excitatory-inhibitory imbalance hypothesis in autism spectrum disorders

It has been proposed that the Glutamate (Glu) system is implicated in autism spectrum disorders (ASD) via an imbalance between excitatory and inhibitory brain circuits, which impacts on brain function. Here, we investigated the excitatory-inhibitory imbalance theory by measuring Glu-concentrations and the relationship with resting-state function. Nineteen adult males with ASD and 19 age and sex-matched healthy controls (HC) (23 - 58 years) underwent Proton Magnetic Resonance Spectroscopy of the dorsal anterior cingulate cortex (dACC) and resting-state functional Magnetic Resonance Imaging (fMRI). Glu and Glx concentrations were compared between groups. Seed-based functional connectivity was analyzed with a priori seeds of the right and left dACC. Finally, metabolite concentrations were related to functional connectivity coefficients and compared between both groups. Individuals with ASD showed significantly negative associations between increased Glx concentrations and reduced functional connectivity between the dACC and insular, limbic and parietal regions. In contrast, HC displayed a positive relationship between the same metabolite and connectivity measures. We provided new evidence to support the excitatory-inhibitory imbalance theory, where excitatory Glx concentrations were related to functional dysconnectivity in ASD. Future research is needed to investigate large-scale functional networks in association with both excitatory and inhibitory metabolites in subpopulations of ASD.

Circadian Rhythm Disorders and Corresponding Functional Brain Abnormalities in Young Female Nurses: A Preliminary Study.

Objective: Shift work is associated with a decrease in melatonin level and perturbation of the circadian rhythm; however, it is unknown if these lead to functional brain changes. In this study, we investigated whether circadian rhythm disorders caused by shift work are related to changes in brain functional connectivity (FC) and regional homogeneity (ReHo) using whole-brain resting-state functional magnetic resonance imaging (fMRI).Methods: This prospective case-control study included nine female night shift nurses and nine age-matched female day work nurses with normal sleep rhythms. To assess sleep quality and mood, participants were asked to complete questionnaires. Serum melatonin and cortisol levels were measured. ReHo of whole-brain resting-state function and seed-based FC of the bilateral hypothalamus were compared between groups. Variables that differed significantly between groups were used to examine the association between questionnaire scores and hormone levels and fMRI data.Results: The night shift nurses had significantly lower sleep quality and melatonin levels; lower ReHo activation in the bilateral cerebellar hemisphere and higher ReHo in the bilateral occipital lobe and left parietal lobe; and higher FC from the hypothalamus to the right cingulate gyrus, right putamen, and vermis than did the day shift nurses. Activation of the right cerebellar hemisphere left superior parietal gyrus, and the right superior occipital gyrus was correlated with sleep quality scores. Moreover, activation of the right cerebellar hemisphere (r = 0.583, P = 0.011) was correlated with melatonin levels, and higher sleepiness scores were associated with stronger FC between the hypothalamus and vermis (r = 0.501, P = 0.034).Conclusions: Circadian rhythm disorder caused by night shift work can lead to a decrease in sleep quality and melatonin level, as well as a series of changes in brain FC and ReHo.

Neurocognitive disorders in the elderly: altered functional resting-state hyperconnectivities in postoperative delirium patients

Postoperative delirium (POD) represents a confusional state during days/weeks after surgery and is particularly frequent in elderly patients. Hardly any fMRI studies were conducted to understand the underlying pathophysiology of POD patients. This prospective observational cohort study aims to examine changes of specific resting-state functional connectivity networks across different time points (pre- and 3–5 months postoperatively) in delirious patients compared to no-POD patients. Two-hundred eighty-three elderly surgical patients underwent preoperative resting-state fMRI (46 POD). One-hundred seventy-eight patients completed postoperative scans (19 POD). For functional connectivity analyses, three functional connectivity networks with seeds located in the orbitofrontal cortex (OFC), nucleus accumbens (NAcc), and hippocampus were investigated. The relationship of POD and connectivity changes between both time points (course connectivity) were examined (ANOVA). Preoperatively, delirious patients displayed hyperconnectivities across the examined functional connectivity networks. In POD patients, connectivities within NAcc and OFC networks demonstrated a decrease in course connectivity [max. F = 9.03, p = 0.003; F = 4.47, p = 0.036, resp.]. The preoperative hyperconnectivity in the three networks in the patients at risk for developing POD could possibly indicate existing compensation mechanisms for subtle brain dysfunction. The observed pathophysiology of network function in POD patients at least partially involves dopaminergic pathways.

The neural substrates of subliminal attentional bias and reduced inhibition in individuals with a higher BMI: A VBM and resting state connectivity study

Previous studies have shown that individuals with overweight and obesity may experience attentional biases and reduced inhibition toward food stimuli. However, evidence is scarce as to whether the attentional bias is present even before stimuli are consciously recognized. Moreover, it is not known whether or not differences in the underlying brain morphometry and connectivity may co-occur with attentional bias and impulsivity towards food in individuals with different BMIs. To address these questions, we asked fifty-three participants (age M = 23.2, SD = 2.9, 13 males) to perform a breaking Continuous Flash Suppression (bCFS) task to measure the speed of subliminal processing, and a Go/No-Go task to measure inhibition, using food and nonfood stimuli. We collected whole-brain structural magnetic resonance images and functional resting-state activity. A higher BMI predicted slower subliminal processing of images independently of the type of stimulus (food or nonfood, p = 0.001, εp2 = 0.17). This higher threshold of awareness is linked to lower grey matter (GM) density of key areas involved in awareness, high-level sensory integration, and reward, such as the orbitofrontal cortex [t = 4.55, p = 0.003], the right temporal areas [t = 4.18, p = 0.002], the operculum and insula [t = 4.14, p = 0.005] only in individuals with a higher BMI. In addition, individuals with a higher BMI exhibit a specific reduced inhibition to food in the Go/No-Go task [p = 0.02, εp2 = 0.02], which is associated with lower GM density in reward brain regions [orbital gyrus, t = 4.97, p = 0.005, and parietal operculum, t = 5.14, p < 0.001] and lower resting-state connectivity of the orbital gyrus to visual areas [fusiform gyrus, t = -4.64, p < 0.001 and bilateral occipital cortex, t = -4.51, p < 0.001 and t = -4.34, p < 0.001]. Therefore, a higher BMI is predictive of non food-specific slower visual subliminal processing, which is linked to morphological alterations of key areas involved in awareness, high-level sensory integration, and reward. At a late, conscious stage of visual processing a higher BMI is associated with a specific bias towards food and with lower GM density in reward brain regions. Finally, independently of BMI, volumetric variations and connectivity patterns in different brain regions are associated with variability in bCFS and Go/No-Go performances.

Lesion-based structural and functional networks in patients with step length asymmetry after stroke

The aim of this study was to determine common structural and functional networks associated with asymmetric step length after unilateral ischemic stroke. Thirty-nine chronic stroke patients were divided into two groups, based on the presence or absence of asymmetric step length. In each group, each lesion was mapped onto a brain magnetic resonance image. The structural and functional networks of brain regions connected to each lesion were identified using a public diffusion tensor and resting state function magnetic resonance image dataset. To identify brain regions associated with asymmetric step length, we conducted voxel-wise independent sample t-tests for structural and function lesion network maps. At least 85% of lesions showed functional network overlap in the bilateral frontal lobe. Functional connectivity of the dorsolateral prefrontal cortex in the contralesional hemisphere was significantly decreased in group 1 compared to that in group 2. The dorsolateral prefrontal cortex may have an important role in compensating for an asymmetric step length after a unilateral stroke.

Cerebral fractional amplitude of low-frequency fluctuations may predict headache intensity improvement following acupuncture treatment in migraine patients.

To explore how baseline resting-state cerebral function predicts clinical outcomes of acupuncture treatment for migraine. One hundred migraine patients and 46 healthy subjects were recruited. Patients were randomized into the acupuncture, sham acupuncture, and waiting list groups. Resting-state functional magnetic resonance imaging data were collected at baseline and after 1 month of longitudinal acupuncture treatments. Fractional amplitude of low-frequency fluctuations (fALFF) calculations were applied to explore the associations between baseline fALFF and changes in clinical variables in the acupuncture treatment group and the waiting list group. Compared with healthy subjects, migraine patients had lower fALFF in the left rostral ventromedial medulla, right thalamus, left amygdala, and right angular gyrus. Regression analyses revealed that baseline fALFF values in the left middle frontal gyrus, left superior temporal gyrus, and middle temporal gyrus were positively associated with headache intensity changes in the acupuncture treatment group, while baseline fALFF values in the bilateral lingual gyrus and cuneus were negatively associated with headache intensity changes in this group. The baseline fALFF values of brain regions associated with cognitive pain modulation, but not migraine severity, may predict future headache intensity improvement levels in migraine patients receiving acupuncture treatment.

Studying the precuneus reveals structure-function-affect correlation in long-term meditators.

Abstract Understanding the relationship between brain structure, function and self-reports has hardly been addressed until now in meditation research. Here we demonstrate such relationship, using Mindfulness meditation (MM). MM aims to reduce thought-related processes and enhance bodily awareness, thereby reducing identification with thought content and deconstructing maladaptive self-schema. We thus hypothesized that structure of the default mode network (DMN) regions, associated with spontaneous thoughts and self-representation, would negatively correlate with MM experience and self-reported positive affect, while positively correlating with DMN resting-state function. Cross-sectionally comparing a unique group of adept MM practitioners and meditation-naive matched controls using voxel based morphometry revealed that gray matter (GM) density of the left precuneus (L-Prc) was negatively correlated with MM expertise. Furthermore, GM density of the L-Prc was positively correlated with resting state and task related functional (fMRI) measures within the L-Prc in the MM practitioners, but not in the controls. Finally, the L-Prc’s GM density negatively correlated with positive affect across all participants. Our findings may shed light on understanding structure-function-self reports relationship. While our approach enables studying suggestive correlations in expert MM practitioners, longitudinal studies are required for direct insights concerning the question of causality. Significance statement Understanding the relationship between brain structure and function, individual differences and self-reports, is an important goal of neuroscience. Yet, these factors were hardly investigated together in meditation research. The precuneus is part of the default mode network (DMN) involved in thought related processes. Mindfulness meditation (MM) is a mental practice aiming to reduce thought related processes. Here, by cross-sectionally comparing adept meditators and controls, we found that in the precuneus of MM practitioners, structure associated with function. Overall, structure negatively correlated with practice length, as well as with positive affect scores. The structure-function correlation was only significant in the meditators group, possibly implying that prolonged meditation improved structure and function attunement in the DMN. More generally, this study demonstrates that mental practice can be related to conjoint structural and functional effects, as well as to affective self-reports.

Resilience, Psychological Characteristics, and Resting-state Brain Cortical Activity in Athletes and Non-athletes

Background: Athletes might build long-term resilience due to their need to adapt constantly to stressful situations. Further, physical activity is a powerful tool for stress-release, and controlling anxiety and depressive symptoms which might induce resilience by enhancing coping skills. Objective: This study aimed to compare the resilience, psychological characteristics, and the resting-state brain cortical activity of athletes and non-athletes. The secondary goal was to identify which variables could predict the resilience score. Methods: Ninety participants were divided into three groups, athlete (n=30), physically active (n=30) and sedentary (n=30), and asked to fill out the international physical activity questionnaire – short version (IPAQ), the resilience scale, the Beck depression inventory (BDI) and the trait and state anxiety inventory (STAI). Moreover, resting-state brain cortical activity was recorded by using an EEG to compute the standardized low-resolution brain electromagnetic tomography (sLORETA) analyses. Results: Significant differences between groups were observed in terms of resilience (X2=8.52; p=0.014) and physical activity level (X 2=76.07; p&lt;0.001), with the athletes presenting higher values. Lower anxiety and depression, and higher physical activity levels were associated with higher resilience scores (R2=0.45; p=0.02). The results of sLORETA showed higher activity for sedentary individuals compared to athletes in frontal areas (Broadmann Area-BA 6, BA 8, BA 9), as well as when compared to physically active individuals in the superior frontal gyrus (BA 9). Additionally, physically active individuals presented less activity than athletes in the inferior occipital gyrus (BA 18). Conclusion: The results suggest that the physically active and athlete groups may have built a more resilient profile (compared to sedentary), have similar anxiety and depressive symptoms, and present a divergent resting-state brain cortical activity from the sedentary group, mainly in prefrontal areas. These findings suggest that regular physical activity and sports should be encouraged to aid in enhancing resilience and resting-state brain cortical function, and consequently, improving mental health.

Long-term Air Pollution and Noise Exposures and Structural Parameters of the Default Mode Network in the 1000BRAINS Study

Background/Aim: While evidence suggests that long-term air pollution (AP) and noise may have negative effects on brain health and cognition, little is known about structural and functional changes in the brain networks that may underlie these associations. We investigated the association between AP and traffic noise exposures and structural parameters, including cortical thickness and the local gyrification index (lGI), of the Default Mode Network (DMN) in the brain, as it is important for resting-state brain function. Like what is seen in the DMN with aging, we hypothesized AP and noise exposures to be associated with decreased cortical thickness and more local atrophy (i.e., lower lGI). Methods: We used data from 559 participants of the 1000BRAINS study in Germany. Residential mean AP exposures (particulate matter [PM] 10, PM2.5, NO2, and accumulation mode particulate number concentration [PNAM]) were modeled for the years 2006-2008 using the validated EURAD chemistry transport model on a 1 km2 scale. Long-term traffic noise was modeled at participants’ homes according to European standards. Cortical thickness and lGI values in the left and right medial prefrontal cortex, posterior cingulate cortex, and inferior parietal lobule of the DMN were calculated from T1-weighted structural brain images collected between 2011 and 2015. Associations between environmental exposures and brain parameters were estimated using linear regression models, adjusting for demographic and lifestyle characteristics. Results: Exposure to PM10, PM2.5 and PNAM was weakly associated with decreased cortical thickness in the left prefrontal cortex (e.g., -0.02 [95% Confidence-Interval: -0.03, 0.00] mm per 3.65 µg/m3 increase in PM10). No associations were observed for AP and lGI or between traffic noise exposure and either DMN parameter. Conclusion: Weak associations between AP and structural parameters of the DMN in the brain were observed, but further studies are needed to validate this result.

Adolescent Resting-State Brain Networks and Unique Variability of Conduct Problems Within the Externalizing Dimension.

The externalizing psychopathological dimension is associated with alterations in adolescents' functional brain connectivity. The current study aims to identify the functional correlates of the unique variability in conduct problems within the context of the broad externalizing dimension. The broad externalizing dimension and unique variability in conduct problems were estimated using a bifactor model. Resting-state data were available for a sample of 125 adolescents. Based on multiresolution parcellation of functional brain networks atlas, major resting-state functional brain networks and the connectivity correlates of unique conduct problems and the broad externalizing dimension were established. The broad externalizing dimension was related to connectivity alterations in the ventral attention/salience network, while unique variability in conduct problems dimension was related to connectivity alterations in the cerebellum crusi as well as the mesolimbic network. The current study is a first step toward the identification of functional resting-state network correlates of broad and specific variability in the externalizing dimension.

A Systematic Review of Cerebral Functional Near-Infrared Spectroscopy in Chronic Neurological Diseases-Actual Applications and Future Perspectives.

Background: The management of people affected by age-related neurological disorders requires the adoption of targeted and cost-effective interventions to cope with chronicity. Therapy adaptation and rehabilitation represent major targets requiring long-term follow-up of neurodegeneration or, conversely, the promotion of neuroplasticity mechanisms. However, affordable and reliable neurophysiological correlates of cerebral activity to be used throughout treatment stages are often lacking. The aim of this systematic review is to highlight actual applications of functional Near-Infrared Spectroscopy (fNIRS) as a versatile optical neuroimaging technology for investigating cortical hemodynamic activity in the most common chronic neurological conditions. Methods: We reviewed studies investigating fNIRS applications in Parkinson’s Disease (PD), Alzheimer’s Disease (AD) and Mild Cognitive Impairment (MCI) as those focusing on motor and cognitive impairment in ageing and Multiple Sclerosis (MS) as the most common chronic neurological disease in young adults. The literature search was conducted on NCBI PubMed and Web of Science databases by PRISMA guidelines. Results: We identified a total of 63 peer-reviewed articles. The AD spectrum is the most investigated pathology with 40 articles ranging from the traditional monitoring of tissue oxygenation to the analysis of functional resting-state conditions or cognitive functions by means of memory and verbal fluency tasks. Conversely, applications in PD (12 articles) and MS (11 articles) are mainly focused on the characterization of motor functions and their association with dual-task conditions. The most investigated cortical area is the prefrontal cortex, since reported to play an important role in age-related compensatory mechanism and neurofunctional changes associated to these chronic neurological conditions. Interestingly, only 9 articles applied a longitudinal approach. Conclusion: The results indicate that fNIRS is mainly employed for the cross-sectional characterization of the clinical phenotypes of these pathologies, whereas data on its utility for longitudinal monitoring as surrogate biomarkers of disease progression and rehabilitation effects are promising but still lacking.

Resting-State Function Connectivity Associated With Being a "Morning-Type" Dementia Caregiver and Having Lower Depression Symptom Severity.

A lack of "morningness" predicts greater depression symptom severity over time, including in a vulnerable group of older adults: family dementia caregivers (dCGs). Evidence regarding the neurobiological basis of these correlations is needed to guide future research towards biomarker-informed detection and prevention approaches. We therefore primarily aimed to identify simple resting-state biomarkers that correlated with a lack of "morningness" in dCGs. We examined 54 dCGs (mean age = 70, range: 61-84; 70% female) of whom 40% were definite "morning types" according to Composite Scale of Morningness (CSM). Using a 7 Tesla resting-state sequence, we compared the functional connectivity of nodes in networks previously implicated in depression (fronto-parietal, default mode, limbic, and salience) between caregivers who were and were not "morning types." Correcting for voxel-wise comparisons, "morning-type" dCGs had less amygdala-posterior cingulate connectivity (Cohen's d = -1.3), which statistically mediated ~32% of the association between the degree of "morningness" and lower depression severity. Post hoc analyses of CSM items found significant correlations, with both amygdala-posterior cingulate FC and depression severity, for 4/6 items pertaining to difficulty, 2/5 items pertaining to preference, and 0/2 items pertaining to typical patterns. Prior research shows that amygdala-posterior cingulate connectivity increases when allocating attention to peripheral aspects of negative emotional stimuli. As such, difficulty with morning activation may relate to the ongoing direction of focus around distressing content; in contrast, morning activity participation may serve to limit focus on distress. Replication and experimental studies are required to confirm these associations and their modifiability.