Resting-state Connectivity Research Articles

Sex-dependent effects of early life stress on reinforcement learning and limbic cortico-striatal functional connectivity

Major depressive disorder (MDD) is a stress-related condition hypothesized to involve aberrant reinforcement learning (RL) with positive and negative stimuli. The present study investigated whether repeated early maternal separation (REMS) stress, a procedure widely recognized to cause depression-like behaviour, affects how subjects learn from positive and negative feedback. The REMS procedure was implemented by separating male and female rats from their dam for 6 h each day from post-natal day 5–19. Control rat offspring were left undisturbed during this period. Rats were tested as adults for behavioral flexibility and feedback sensitivity on a probabilistic reversal learning task. A computational approach based on RL theory was used to derive latent behavioral variables related to reward learning and flexibility. To assess underlying brain substrates, a seed-based functional MRI connectivity analysis was applied both before and after an additional adulthood stressor in control and REMS rats. Female but not male rats exposed to REMS stress showed increased response ‘stickiness’ (repeated responses regardless of reward outcome). Following repeated adulthood stress, reduced functional connectivity from the basolateral amygdala (BLA) to the dorsolateral striatum (DLS), cingulate cortex (Cg), and anterior insula (AI) cortex was observed in females. By contrast, control male rats exposed to the second stressor showed impaired learning from negative feedback (i.e., non-reward) and reduced functional connectivity from the BLA to the DLS and AI compared to maternally separated males. RL in male rats exposed to REMS was unaffected. The fMRI data further revealed that connectivity between the mOFC and other prefrontal cortical and subcortical structures was positively correlated with response ‘stickiness’. These findings reveal differences in how females and males respond to early life adversity and subsequent stress. These effects may be mediated by functional divergence in resting-state connectivity between the basolateral amygdala and fronto-striatal brain regions.

Effects of gastric bypass surgery on brain connectivity responses to hypoglycemia

IntroductionRoux-en-Y gastric bypass (RYGB) leads to beneficial effects on glucose homeostasis, and attenuated hormonal counterregulatory responses to hypoglycemia are likely to contribute. RYGB also induces alterations in neural activity of cortical and subcortical brain regions. We aimed to characterize RYGB-induced changes in resting-state connectivity of specific brain regions of interest for energy homeostasis and behavioral control during hypoglycemia.MethodTen patients with BMI > 35 kg/m2 were investigated with brain PET/MR imaging during a hyperinsulinemic normo- and hypoglycemic clamp, before and 4 months after RYGB. Hormonal levels were assessed throughout the clamp. Resting-state (RS) fMRI scans were acquired in the glucose-lowering phase of the clamp, and they were analyzed with a seed-to-voxel approach.ResultsRS connectivity during initiation of hypoglycemia was significantly altered after RYGB between nucleus accumbens, thalamus, caudate, hypothalamus and their crosstalk with cortical and subcortical regions. Connectivity between the nucleus accumbens and the frontal pole was increased after RYGB, and this was associated with a reduction of ACTH (r = −0.639, p = 0.047) and cortisol (r = −0.635, p = 0.048) responses. Instead, connectivity between the caudate and the frontal pole after RYGB was reduced and this was associated with less attenuation of glucagon response during the hypoglycemic clamp (r = −0.728, p = 0.017), smaller reduction in fasting glucose (r = −0.798, p = 0.007) and less excess weight loss (r = 0.753, p = 0.012). No other significant associations were found between post-RYGB changes in ROI-to-voxel regional connectivity hormonal responses and metabolic or anthropometric outcomes.ConclusionRYGB alters brain connectivity during hypoglycemia of several neural pathways involved in reward, inhibitory control, and energy homeostasis. These changes are associated with altered hormonal responses to hypoglycemia and may be involved in the glucometabolic outcome of RYGB.

Functional connectivity between mesial temporal and default mode structures may help lateralize surgical temporal lobe epilepsy.

The most common surgically treatable epilepsy syndrome is mesial temporal lobe epilepsy (mTLE). Preoperative noninvasive lateralization of mTLE is challenging in part due to rapid contralateral seizure spread. Abnormal connections in both the mesial temporal lobe and resting-state networks have been described in mTLE, but it is unclear if connectivity between these networks may aid in lateralization. In 52 patients with left mTLE (LmTLE) or right mTLE (RmTLE) and 52 matched control subjects, the authors acquired 20 minutes of resting-state functional MRI (fMRI) and evaluated functional connectivity of bilateral hippocampi and amygdalae with selected resting-state networks. They used Pearson correlation, network-based statistic, and dynamic causal modeling. Also, to evaluate the clinical utility of a resting-state connectivity model in lateralizing unilateral presurgical mTLE patients, they used receiver operating characteristic curve analysis. RmTLE patients demonstrated decreased nondirected connectivity between the right hippocampus and default mode network compared with LmTLE patients and control subjects. Network-based statistic analysis revealed that the network with most decreased connectivity that distinguished LmTLE from RmTLE patients included the right hippocampus and amygdala, right lateral orbitofrontal cortices, and bilateral inferior parietal lobules, precuneus, and medial orbitofrontal cortices. Dynamic causal modeling analysis revealed that cross-hemispheric connectivity between hippocampi and amygdalae was predominantly inward toward the epileptogenic side. A regression model incorporating these connectivity patterns was used to accurately lateralize mTLE patients with an area under the receiver operating characteristic curve of 0.87. Evaluating fMRI connectivity between mesial temporal structures and default mode network may aid in mTLE lateralization, reduce need for intracranial monitoring, and guide surgical planning.

Cerebellar correlates of social dysfunction among individuals at clinical high risk for psychosis.

Social deficits are a significant feature among both individuals with psychosis and those at clinical high-risk (CHR) for developing psychosis. Critically, the psychosis risk syndrome emerges in adolescence and young adulthood, when social skill development is being fine-tuned. Yet, the underlying pathophysiology of social deficits in individuals at CHR for psychosis remains unclear. Literature suggests the cerebellum plays a critical role in social functioning. Cerebellar dysfunction in psychosis and CHR individuals is well-established, yet limited research has examined links between the cerebellum and social functioning deficits in this critical population. In the current study, 68 individuals at CHR for developing psychosis and 66 healthy controls (HCs) completed social processing measures (examining social interaction, social cognition, and global social functioning) and resting-state MRI scans. Seed-to-voxel resting-state connectivity analyses were employed to examine the relationship between social deficits and lobular cerebellar network connectivity. Analyses indicated that within the CHR group, each social domain variable was linked to reduced connectivity between social cerebellar subregions (e.g., Crus II, lobules VIIIa and VIIIb) and cortical regions (e.g., frontal pole and frontal gyrus), but a control cerebellar subregion (e.g., lobule X) and was unrelated to these social variables. These results indicate an association between several cerebellar lobules and specific deficits in social processing. The cerebellum, therefore, may be particularly salient to the social domain and future research is need to examine the role of the cerebellum in psychosis.

Investigating the effects of antipsychotics on brain insulin action: Study protocol for a multi-modality magnetic resonance imaging (MRI) study in healthy controls.

Antipsychotics (APs) are the cornerstone of treatment for schizophrenia (SCZ) but are unfortunately associated with serious metabolic adverse effects including weight gain and type 2 diabetes. The pathophysiology of AP-induced metabolic dysfunction is largely undetermined. Brain insulin resistance has been posited to be at the cross-roads of many cognitive and metabolic disorders, and disruption of central insulin action has emerged as a possible explanatory mechanism underlying AP induced metabolic dysfunction. Previous studies suggest that change in neuroimaging-based parameters with intranasal insulin administration can be leveraged to investigate brain insulin resistance. In this proof-of-concept study, we will utilize neural signatures of insulin action in the brain to examine if APs disrupt brain insulin signaling. It is hypothesized that: 1) intranasal insulin (INI), but not intranasal placebo (INP), will change cerebral blood flow and resting state connectivity, as well as increase glutamate levels in the striatum and dorsolateral prefrontal cortex; 2) oral olanzapine (OLA), but not oral placebo (PL), will inhibit the effect of INI on these parameters. Thirty-two healthy volunteers will undergo a single blind, cross-over design, wherein all participants receive the following four treatment combinations, 2-6 weeks apart, in a random sequence: INP + PL, INP + OLA, INI + PL, and INI + OLA. Participants will undergo an MRI-based assay of brain insulin resistance 15 minutes after administering 160 IU INI or INP. The scanning protocol includes resting and task-based functional MRI, arterial spin labelling, and proton magnetic resonance spectroscopy. Demonstrating that OLA can acutely induce brain insulin resistance is clinically relevant to metabolic health in SCZ. Evidence of brain insulin resistance induced by acute AP dosing can inform the early use of adjunctive insulin sensitizers for the treatment of metabolic comorbidities associated with AP treatment in severe mental illness. Trial registration ClinicalTrials.gov Registration: NCT03741478.

The relationship between brain neural correlates, self-objectification, and interoceptive sensibility

Interoceptive sensibility refers to the tendency to focus on internal bodily states and the capacity to detect them. As the subjective dimension of interoception, interoceptive sensibility plays a key role in individuals’ health. Self-objectification, a process by which individuals tend to adopt a third-person’s perspective of their physical self, leads to decreased interoceptive sensibility. However, few studies regarding the neural basis of interoceptive sensibility and the underlying mechanism of the relationship between self-objectification and interoceptive sensibility have been conducted. In this study, we assessed the resting-state brain activity (fractional amplitude of low-frequency fluctuation, fALFF) and connectivity (resting-state functional connectivity, RSFC) of 442 college students. Whole-brain correlation analyses revealed that a higher level of interoceptive sensibility was linked to higher fALFF in the right inferior frontal gyrus (IFG) and left cerebellum and to lower fALFF in the left paracentral lobule and left superior/middle temporal gyrus. Interoceptive sensibility also was negatively associated with the RSFC between the right IFG and the right secondary somatosensory cortex (S2) and the right IFG and the ventral premotor cortex (VPC). These brain regions and connections are mainly responsible for switching attention to internal/external information and processing body-related somatosensory as well as sensory information. Mediation analyses suggested that the fALFF of the right IFG and the RSFC of IFG-S2 and IFG-VPC mediated the relationship between self-objectification and interoceptive sensibility. Overall, these results suggest that the IFG may be the neural marker of interoceptive sensibility and reveal several potential mediation models of the relationship between brain neural correlates and self-objectification and interoceptive sensibility.

Brain structure and connectivity in psoriasis and associations with depression and inflammation; findings from the UK biobank

BackgroundPsoriasis is a chronic systemic inflammatory skin disease, coexisting with depression in up to 25% of patients. Little is known about the drivers of comorbidity, including shared neurobiology and depression brain imaging patterns in patients. An immune-mediated crosstalk between the brain and skin has been hypothesized in psoriasis. With the aim of investigating brain structure and connectivity in psoriasis in relation to depression comorbidity, we conducted a brain imaging study including the largest psoriasis patient sample to date (to our knowledge) and the first to investigate the role of depression and systemic inflammation in brain measures. Effects of coexisting psoriatic arthritis (PsA), which represents joint involvement in psoriasis and a higher putative inflammatory state, were further explored. MethodsBrain magnetic resonance imaging (MRI) data of 1,048 UK Biobank participants were used (131 comorbid patients with psoriasis and depression, age-and sex-matched to: 131 non-depressed psoriasis patients; 393 depressed controls; and 393 non-depressed controls). Interaction effects of psoriasis and depression on volume, thickness and surface of a-priori defined regions of interest (ROIs), white matter tracts and 55x55 partial correlation resting-state connectivity matrices were investigated using general linear models. Linear regression was employed to test associations of brain measures with C-reactive protein (CRP) and neutrophil counts. ResultsNo differences in regional or global brain volumes or white matter integrity were found in patients with psoriasis compared to controls without psoriasis or PsA. Thickness in right precuneus was increased in psoriasis patients compared to controls, only when depression was present (β = 0.26, 95% CI [Confidence Intervals] 0.08, 0.44; p = 0.02). In further analysis, psoriasis patients who had PsA exhibited fronto-occipital decoupling in resting-state connectivity compared to patients without joint involvement (β = 0.39, 95% CI 0.13, 0.64; p = 0.005) and controls (β = 0.49, 95% CI 0.25, 0.74; p < 0.001), which was unrelated to depression comorbidity. Precuneus thickness and fronto-occipital connectivity were not predicted by CRP or neutrophil counts. Precuneus thickening among depressed psoriasis patients showed a marginal correlation with recurrent lifetime suicidality. ConclusionsOur findings provide evidence for a combined effect of psoriasis and depression on the precuneus, which is not directly linked to systemic inflammation, and may relate to suicidality or altered somatosensory processing. The use of the UK Biobank may limit generalizability of results in populations with severe disease.

Mechanisms of imbalanced frontostriatal functional connectivity in obsessive-compulsive disorder.

The diagnosis of obsessive-compulsive disorder (OCD) has been linked with changes in frontostriatal resting-state connectivity. However, replication of prior findings is lacking, and the mechanistic understanding of these effects is incomplete. To confirm and advance knowledge on changes in frontostriatal functional connectivity in OCD, participants with OCD and matched healthy controls underwent resting-state functional, structural and diffusion neuroimaging. Functional connectivity changes in frontostriatal systems were here replicated in individuals with OCD (n = 52) compared with controls (n = 45). OCD participants showed greater functional connectivity (t = 4.3, PFWE = 0.01) between the nucleus accumbens (NAcc) and the orbitofrontal cortex (OFC) but lower functional connectivity between the dorsal putamen and lateral prefrontal cortex (t = 3.8, PFWE = 0.04) relative to controls. Computational modelling suggests that NAcc-OFC connectivity changes reflect an increased influence of NAcc over OFC activity and reduced OFC influence over NAcc activity (posterior probability, Pp > 0.66). Conversely, dorsal putamen showed reduced modulation over lateral prefrontal cortex activity (Pp > 0.90). These functional deregulations emerged on top of a generally intact anatomical substrate. We provide out-of-sample replication of opposite changes in ventro-anterior and dorso-posterior frontostriatal connectivity in OCD and advance the understanding of the neural underpinnings of these functional perturbations. These findings inform the development of targeted therapies normalizing frontostriatal dynamics in OCD.

Neural Networks Implicated in Autobiographical Memory Training.

Training of autobiographical memory has been proposed as an intervention to improve cognitive function. The neural substrates for such improvements are poorly understood. Several brain areas have been previously linked to autobiographical recollection, including structures in the default mode network (DMN) and the sensorimotor network. Here, we tested the hypothesis that changes in connectivity within different neural networks support distinct aspects of memory improvement in response to training on a group of 59 human subjects. We found that memory training using olfactory cues increases resting-state intranetwork DMN connectivity, and this associates with improved recollection of cue-specific memories. On the contrary, training decreased resting-state connectivity within the sensorimotor network, a decrease that correlated with improved ability for voluntary recall. Moreover, preliminary data indicate that only the decrease in sensorimotor connectivity associated with the training-induced decrease in the tumor necrosis factor α (TNFα) factor, an immune modulation previously linked to improved cognitive performance. We identified functional and biochemical factors that associate with distinct memory processes improved by autobiographical training. Pathways which connect autobiographical memory with both high-level cognition and somatic physiology are discussed.

Hyperconnectivity matters in early-onset Alzheimer's disease: a resting-state EEG connectivity study

ObjectivesThe aim of this study was to differentiate individuals with early-onset Alzheimer's disease (EOAD) and identify differences of functional connectivity in resting-state EEG between individuals with EOAD and late-onset AD (LOAD) in comparison with both healthy young and elderly individuals. MethodsForty EOAD and 56 LOAD patients were included along with 51 demographically matched young, and 54 elderly healthy individuals as controls to the EOAD and LOAD groups. Four minutes of resting-state EEG were recorded during the eyes-closed condition. The absolute value of imaginary coherence (ICoh) was measured for connectivity. The maximum values of ICoh were measured at delta (0.5-3.5 Hz), theta (4-7.5Hz), alpha (8-13 Hz), alpha-1 (8-10 Hz), alpha-2 (10.5-13 Hz), beta (13-30 Hz), beta-1 (13-20 Hz), and beta-2 (20.5-30 Hz) frequency bands. ResultsIndividuals with EOAD showed higher coherence values in all frequency bands than LOAD patients. Compared to young healthy controls (YHC), EOAD had increased ICoh values in theta and beta-2 bands, whereas LOAD had lower ICoh values in the alpha-1 band than elderly healthy controls (EHC). Lastly, patients with EOAD demonstrated negative moderate correlations between language domains and beta-1 ICoh values. ConclusionTo the authors’ knowledge, this is the first study evaluating coherence alterations among early-and late-onset AD patients and the diagnostic value of coherence measures. It was suggested that EOAD patients had more severe pathological changes compared with LOAD.

Self-Referential Processing and Resting-State Functional MRI Connectivity of Cortical Midline Structures in Glioma Patients.

Metacognition has only scarcely been investigated in brain tumor patients. It is unclear if and how the tumor-lesioned brain might be able to maintain an adequate sense-of-self. As cortical midline structures (CMS) are regarded as essential for self-referential mental activity, we investigated resting-state fMRI connectivity (FC) of CMS to the default-mode network (DMN) and to the whole brain, comparing glioma patients and matched controls. Subjects furthermore performed a trait judgement (TJ), a trait recall task (TR), and neuropsychological testing. In the TJ, adjectives had to be ascribed as self- or non-self-describing, assessing the self-serving effect (SSE), a normally observed bias for positive traits. In the TR, the mnemic neglect effect (MNE), a memory advantage for positive traits, was tested. The groups were compared and partial correlations between FC and test metrics were analyzed. Although patients were significantly impaired in terms of verbal memory, groups did not differ in the SSE or the MNE results, showing preserved metacognitive abilities in patients. FC of CMS to the DMN was maintained, but was significantly decreased to whole brain in the patients. FC of the dorsomedial prefrontal cortex (DMPFC) to whole brain was correlated with the MNE in patients. Preserving the DMPFC in therapeutic interventions might be relevant for maintaining self-related verbal information processing in the memory domain in glioma patients.

Additive and Interactive Effects of Attention-Deficit/Hyperactivity Disorder and Tic Disorder on Brain Connectivity

BackgroundAttention-deficit/hyperactivity disorder (ADHD) and persistent tic disorder (PTD) are two neurodevelopmental disorders that frequently co-occur. Contributions of each disorder to cognitive and behavioral deficits have been reported. In this paper, we tested 3 models of pathophysiology for the two disorders (additive, interactive, and phenotypic) using resting-state connectivity associated with each disorder separately and together. MethodsParticipants were 148 children (55 with ADHD only, 33 with ADHD and PTD, 27 with PTD only, and 33 healthy control subjects) at ages 8 to 12 years. Following diagnostic interviews and behavioral assessment, participants underwent a 128-channel electroencephalography recording. Resting-state, cortical source-level effective connectivity was analyzed across the 4 groups using a 2 × 2 factorial design with factors of ADHD (with/without) and PTD (with/without). ResultsADHD diagnosis was the primary driver of cognitive and behavioral deficits, while deficits associated with PTD were primarily with thought problems and internalizing problems when compared with controls. Subadditive effects were observed in co-occurring ADHD+PTD for parent-rated behavioral problems and cognitive functions. Aberrant effective connectivity was primarily associated with ADHD, more specifically with lower posterior and occipital-frontal connectivity, while children with PTD exhibited greater left postcentral to precuneus connectivity. Weaker ADHD-related connectivity was associated with more severe behavioral problems, including internalizing behaviors, thought problems, and working memory deficits. ConclusionsSimilar to general behavioral deficits, aberrant resting-state neural connectivity in pediatric ADHD and PTD combines additively in co-occurring cases. The findings of this study support ADHD as a focus of treatment in comorbid cases, given the driving role of ADHD in both behavioral and neurophysiological deficits.

Striatal resting-state connectivity after long-term diacetylmorphine treatment in opioid-dependent patients.

New treatment approaches for opioid-dependent patients include injectable opioid agonist treatment with diacetylmorphine. While evidence has shown beneficial clinical effects of diacetylmorphine, it is still not clear how long-term diacetylmorphine treatment affects the brain and whether functional brain changes are accompanied by clinical improvements. Therefore, this prospective case-control study focuses on long-term effects of diacetylmorphine on resting-state functional connectivity. We included opioid-dependent patients (N = 22, age range 33-58, 16 males) treated with diacetylmorphine and healthy controls (N = 9, age range 27-55, 5 males) that underwent two MRI assessments approximately nine years apart. For the patients, the assessments took part shortly after the diacetylmorphine intake to be able to explore changes in resting-state functional connectivity in brain regions related to the stage of binge and intoxication (caudate, putamen, nucleus accumbens). A cluster in the right superior frontal gyrus was detected, showing over nine years an increase in functional connectivity originating from the left caudate and the left accumbens in patients but not in healthy controls. These connectivity changes in patients were related to the duration of the diacetylmorphine treatment at the follow-up, indicating smaller increases in functional connectivity with longer treatment duration (r = 0.63, P < 0.01). These results suggest that long-term diacetylmorphine treatment in opioid-dependent patients increases fronto-striatal connections, an effect that is linked to the duration of the treatment duration. Future research needs to further address the wide-ranging effects of diacetylmorphine on brain functioning and deepen the understanding of their clinical relevance.

Trait related aberrant connectivity in clinically stable patients with schizophrenia: A seed based resting state fMRI study

Aberrant resting-state connectivity within and between the Default Mode Network, the Executive Control Network, and the Salience Network is well-established in schizophrenia. Meta-analyses have identified that bilateral lingual gyrus is as the only region showing hyperactivity in schizophrenia and there are reports of increased connectivity between the lingual gyrus and other brain regions in schizophrenia. It is not clear whether these abnormalities represent state or trait markers of the illness, i.e., if they are only present during the acute phase of the illness (state) or if they reflect a predisposition to schizophrenia (trait). In this study, we used a seed-based functional connectivity analysis to investigate brain networks in schizophrenia patients who are in the stable phase of their illness and assess functional connectivity using seeds in the lingual gyrus, the posterior cingulate, the right dorsolateral prefrontal cortex (dlPFC), the right anterior insula (rAI) and the right orbital frontoinsula. Twenty patients with schizophrenia in a stable phase of their illness (as defined by the course of illness and Signs and Symptoms of Psychotic Illness (SSPI) scores) and 20 age and sex-matched healthy controls underwent resting-state functional Magnetic Resonance Imaging (rs-fMRI). Data was analysed using the Data Processing Assistant for Resting-State fMRI Advanced Edition (DPARSFA) V3.1 (http://rfmri.org/DPARSF) and the statistical parametric mapping software 8 (SPM8). Compared with healthy controls, patients with schizophrenia showed increased connectivity between the left lingual gyrus and the middle frontal gyrus, and the cingulate cortex. Lingual gyrus hyper-connectivity may be a stable trait neuroimaging marker for schizophrenia. Our findings suggest that aberrant connectivity in major resting-state networks may not be present after the acute illness has stabilised.

Transcranial direct current stimulation modulates working memory and prefrontal-insula connectivity after mild-moderate traumatic brain injury.

Background: Persistent posttraumatic symptoms (PPS) may manifest after a mild-moderate traumatic brain injury (mmTBI) even when standard brain imaging appears normal. Transcranial direct current stimulation (tDCS) represents a promising treatment that may ameliorate pathophysiological processes contributing to PPS.Objective/Hypothesis: We hypothesized that in a mmTBI population, active tDCS combined with training would result in greater improvement in executive functions and post-TBI cognitive symptoms and increased resting state connectivity of the stimulated region, i.e., left dorsolateral prefrontal cortex (DLPFC) compared to control tDCS.Methods: Thirty-four subjects with mmTBI underwent baseline assessments of demographics, symptoms, and cognitive function as well as resting state functional magnetic resonance imaging (rsfMRI) in a subset of patients (n = 24). Primary outcome measures included NIH EXAMINER composite scores, and the Neurobehavioral Symptom Inventory (NSI). All participants received 10 daily sessions of 30 min of executive function training coupled with active or control tDCS (2 mA, anode F3, cathode right deltoid). Imaging and assessments were re-obtained after the final training session, and assessments were repeated after 1 month. Mixed-models linear regression and repeated measures analyses of variance were calculated for main effects and interactions.Results: Both active and control groups demonstrated improvements in executive function (EXAMINER composite: p < 0.001) and posttraumatic symptoms (NSI cognitive: p = 0.01) from baseline to 1 month. Active anodal tDCS was associated with greater improvements in working memory reaction time compared to control (p = 0.007). Reaction time improvement correlated significantly with the degree of connectivity change between the right DLPFC and the left anterior insula (p = 0.02).Conclusion: Anodal tDCS improved reaction time on an online working memory task in a mmTBI population, and decreased connectivity between executive network and salience network nodes. These findings generate important hypotheses for the mechanism of recovery from PPS after mild-moderate TBI.

Default-Mode Network Connectivity Changes During the Progression Toward Alzheimer's Dementia: A Longitudinal Functional Magnetic Resonance Imaging Study.

Background/Purpose: Brain function changes with Alzheimer's disease (AD) progression. Evaluating those changes longitudinally is important to understand the complex relationships between brain pathologies and cognition. We aimed (1) to identify longitudinal changes in functional connectivity in patients with mild cognitive impairment (MCI) characterized for amyloid-β (Aβ) status and (2) to relate these functional changes to clinical progression. Methods: Forty-four patients with MCI were followed using serial functional magnetic resonance imaging (fMRI) over 1.2 years (three sessions) and cognitive testing over 3.1 years (five sessions). Intra and inter-network connectivities were computed to assess changes in brain connectivity using a network atlas adapted for late adulthood. Sixteen low-Aβ clinically normal older adults underwent a single fMRI session for group comparisons at baseline. Linear mixed-effects models with random intercept and slope were used to predict changes in connectivity based on Aβ status and progression to dementia. Results: At baseline, intra and inter-network resting-state fMRI connectivities did not differ by baseline clinical diagnosis, Aβ status, or clinical progression to dementia. At the final imaging session, progressive MCI had significantly higher connectivity compared with stable MCI, specifically within the default-mode network (DMN). Longitudinally, progressive MCI had increasing intra-DMN connectivity over time compared with stable MCI, and the rate of changes in connectivity was significantly associated with the rate of cognitive decline. Conclusions: Intra-DMN connectivity increases in MCI patients progressing toward dementia, suggesting aberrant synchronization in the symptomatic stages of AD. Impact statement Changes in functional connectivity occur in the course of Alzheimer's disease. We observed a progressive increase over time in resting-state functional connectivity within the default-mode network in patients with mild cognitive impairment who progressed to dementia. The rate of connectivity increase was significantly associated with the rate of cognitive decline. The observation of increased functional connectivity during the progression to dementia, and not only in the pre-clinical stage, is interpreted as an aberrant synchronization rather than a compensation mechanism.

Task-based co-activation patterns reliably predict resting state canonical network engagement during development

Neurodevelopmental research has traditionally focused on development of individual structures, yet multiple lines of evidence indicate parallel development of large-scale systems, including canonical neural networks (i.e., default mode, frontoparietal). However, the relationship between region- vs. network-level development remains poorly understood. The current study tests the ability of a recently developed multi-task coactivation matrix approach to predict canonical resting state network engagement at baseline and at two-year follow-up in a large and cohort of young adolescents. Pre-processed tabulated neuroimaging data were obtained from the Adolescent Brain and Cognitive Development (ABCD) study, assessing youth at baseline (N = 6073, age = 10.0 ± 0.6 years, 3056 female) and at two-year follow-up (N = 3539, age = 11.9 ± 0.6 years, 1726 female). Individual multi-task co-activation matrices were constructed from the beta weights of task contrasts from the stop signal task, the monetary incentive delay task, and emotional N-back task. Activation-based predictive modeling, a cross-validated machine learning approach, was adopted to predict resting-state canonical network engagement from multi-task co-activation matrices at baseline. Note that the tabulated data used different parcellations of the task fMRI data (“ASEG” and Desikan) and the resting-state fMRI data (Gordon). Despite this, the model successfully predicted connectivity within the default mode network (DMN, rho = 0.179 ± 0.002, p < 0.001) across participants and identified a subset of co-activations within parietal and occipital macroscale brain regions as key contributors to model performance, suggesting an underlying common brain functional architecture across cognitive domains. Notably, predictive features for resting-state connectivity within the DMN identified at baseline also predicted DMN connectivity at two-year follow-up (rho = 0.258). These results indicate that multi-task co-activation matrices are functionally meaningful and can be used to predict resting-state connectivity. Interestingly, given that predictive features within the co-activation matrices identified at baseline can be extended to predictions at a future time point, our results suggest that task-based neural features and models are valid predictors of resting state network level connectivity across the course of development. Future work is encouraged to verify these findings with more consistent parcellations between task-based and resting-state fMRI, and with longer developmental trajectories.

Brain adaptation following various unilateral vocal fold paralysis treatments: A magnetic resonance imaging based longitudinal case series.

AimExamination of central compensatory mechanisms following peripheral vocal nerve injury and recovery is essential to build knowledge about plasticity of the neural network underlying phonation. The objective of this prospective multiple-cases longitudinal study is to describe brain activity in response to unilateral vocal fold paralysis (UVFP) management and to follow central nervous system adaptation over time in three patients with different nervous and vocal recovery profiles.Materials and methodsParticipants were enrolled within 3 months of the onset of UVFP. Within 1 year of the injury, the first patient did not recover voice or vocal fold mobility despite voice therapy, the second patient recovered voice and mobility in absence of treatment and the third patient recovered voice and vocal fold mobility following an injection augmentation with hyaluronic acid in the paralyzed vocal fold. These different evolutions allowed comparison of individual outcomes according to nervous and vocal recovery. All three patients underwent functional magnetic resonance imaging (fMRI task and resting-state) scans at three (patient 1) or four (patients 2 and 3) time points. The fMRI task included three conditions: a condition of phonation and audition of the sustained [a:] vowel for 3 s, an audition condition of this vowel and a resting condition. Acoustic and aerodynamic measures as well as laryngostroboscopic images and laryngeal electromyographic data were collected.Results and conclusionThis study highlighted for the first time two key findings. First, hyperactivation during the fMRI phonation task was observed at the first time point following the onset of UVFP and this hyperactivation was related to an increase in resting-state connectivity between previoulsy described phonatory regions of interest. Second, for the patient who received an augmentation injection in the paralyzed vocal fold, we subsequently observed a bilateral activation of the voice-related nuclei in the brainstem. This new observation, along with the fact that for this patient the resting-state connectivity between the voice motor/sensory brainstem nuclei and other brain regions of interest correlated with an aerodynamic measure of voice, support the idea that there is a need to investigate whether the neural recovery process can be enhanced by promoting the restoration of proprioceptive feedback.

Resting-state magnetoencephalographic oscillatory connectivity to identify patients with chronic migraine using machine learning

To identify and validate the neural signatures of resting-state oscillatory connectivity for chronic migraine (CM), we used machine learning techniques to classify patients with CM from healthy controls (HC) and patients with other pain disorders. The cross-sectional study obtained resting-state magnetoencephalographic data from 240 participants (70 HC, 100 CM, 35 episodic migraine [EM], and 35 fibromyalgia [FM]). Source-based oscillatory connectivity of relevant cortical regions was calculated to determine intrinsic connectivity at 1–40 Hz. A classification model that employed a support vector machine was developed using the magnetoencephalographic data to assess the reliability and generalizability of CM identification. In the findings, the discriminative features that differentiate CM from HC were principally observed from the functional interactions between salience, sensorimotor, and part of the default mode networks. The classification model with these features exhibited excellent performance in distinguishing patients with CM from HC (accuracy ≥ 86.8%, area under the curve (AUC) ≥ 0.9) and from those with EM (accuracy: 94.5%, AUC: 0.96). The model also achieved high performance (accuracy: 89.1%, AUC: 0.91) in classifying CM from other pain disorders (FM in this study). These resting-state magnetoencephalographic electrophysiological features yield oscillatory connectivity to identify patients with CM from those with a different type of migraine and pain disorder, with adequate reliability and generalizability.

Genetic and environmental factors influencing neonatal resting-state functional connectivity.

Functional magnetic resonance imaging has been used to identify complex brain networks by examining the correlation of blood-oxygen-level-dependent signals between brain regions during the resting state. Many of the brain networks identified in adults are detectable at birth, but genetic and environmental influences governing connectivity within and between these networks in early infancy have yet to be explored. We investigated genetic influences on neonatal resting-state connectivity phenotypes by generating intraclass correlations and performing mixed effects modeling to estimate narrow-sense heritability on measures of within network and between-network connectivity in a large cohort of neonate twins. We also used backwards elimination regression and mixed linear modeling to identify specific demographic and medical history variables influencing within and between network connectivity in a large cohort of typically developing twins and singletons. Of the 36 connectivity phenotypes examined, only 6 showed narrow-sense heritability estimates greater than 0.10, with none being statistically significant. Demographic and obstetric history variables contributed to between- and within-network connectivity. Our results suggest that in early infancy, genetic factors minimally influence brain connectivity. However, specific demographic and medical history variables, such as gestational age at birth and maternal psychiatric history, may influence resting-state connectivity measures.