Functional Connectivity of the Nucleus Accumbens across Variants of Callous-Unemotional Traits: A Resting-State fMRI Study in Children and Adolescents

A large body of literature suggests that the primary (high callousness-unemotional traits [CU] and low anxiety) and secondary (high CU traits and anxiety) variants of psychopathy significantly differ in terms of their clinical profiles. However, little is known about their neurobiological differences. While few studies showed that variants differ in brain activity during fear processing, it remains unknown whether they also show atypical functioning in motivational and reward system. Latent Profile Analysis (LPA) was conducted on a large sample of adolescents (n = 1416) to identify variants based on their levels of callousness and anxiety. Seed-to-voxel connectivity analysis was subsequently performed on resting-state fMRI data to compare connectivity patterns of the nucleus accumbens across subgroups. LPA failed to identify the primary variant when using total score of CU traits. Using a family-wise cluster correction, groups did not differ on functional connectivity. However, at an uncorrected threshold the secondary variant showed distinct functional connectivity between the nucleus accumbens and posterior insula, lateral orbitofrontal cortex, supplementary motor area, and parietal regions. Secondary LPA analysis using only the callousness subscale successfully distinguish both variants. Group differences replicated results of deficits in functional connectivity between the nucleus accumbens and posterior insula and supplementary motor area, but additionally showed effect in the superior temporal gyrus which was specific to the primary variant. The current study supports the importance of examining the neurobiological markers across subgroups of adolescents at risk for conduct problems to precise our understanding of this heterogeneous population.

Precision data-driven modeling of cortical dynamics reveals idiosyncratic mechanisms underlying canonical oscillations

Task-free brain activity affords unique insight into the functional structure of brain network dynamics and is a strong marker of individual differences. In this work, we present an algorithmic optimization framework that makes it possible to directly invert and parameterize brain-wide dynamical-systems models involving hundreds of interacting brain areas, from single-subject time-series recordings. This technique provides a powerful neurocomputational tool for interrogating mechanisms underlying individual brain dynamics ("precision brain models") and making quantitative predictions. We extensively validate the models' performance in forecasting future brain activity and predicting individual variability in key M/EEG markers. Lastly, we demonstrate the power of our technique in resolving individual differences in the generation of alpha and beta-frequency oscillations. We characterize subjects based upon model attractor topology and a dynamical-systems mechanism by which these topologies generate individual variation in the expression of alpha vs. beta rhythms. We trace these phenomena back to global variation in excitation-inhibition balance, highlighting the explanatory power of our framework in generating mechanistic insights.

Impacts of adrenarcheal DHEA levels on spontaneous cortical activity during development

Dehydroepiandrosterone (DHEA) production is closely associated with the first pubertal hormonal event, adrenarche. Few studies have documented the relationships between DHEA and functional brain development, with even fewer examining the associations between DHEA and spontaneous cortical activity during the resting-state. Thus, whether DHEA levels are associated with the known developmental shifts in the brain's idling cortical rhythms remains poorly understood. Herein, we examined spontaneous cortical activity in 71 typically-developing youth (9-16 years; 32 male) using magnetoencephalography (MEG). MEG data were source imaged and the power within five canonical frequency bands (delta, theta, alpha, beta, gamma) was computed to identify spatially- and spectrally-specific effects of salivary DHEA and DHEA-by-sex interactions using vertex-wise ANCOVAs. Our results indicated robust increases in power with increasing DHEA within parieto-occipital cortices in all frequency bands except alpha, which decreased with increasing DHEA. In the delta band, DHEA and sex interacted within frontal and temporal cortices such that with increasing DHEA, males exhibited increasing power while females showed decreasing power. These data suggest that spontaneous cortical activity changes with endogenous DHEA levels during the transition from childhood to adolescence, particularly in sensory and attentional processing regions. Sexually-divergent trajectories were only observed in later-developing frontal cortical areas.

Three-year reliability of MEG resting-state oscillatory power

Introduction:

Resting-state oscillatory activity has been extensively studied across a wide array of disorders. Establishing which spectrally- and spatially-specific oscillatory components exhibit test-retest reliability is essential to move the field forward. While studies have shown short-term reliability of MEG resting-state activity, no studies have examined test-retest reliability across an extended period of time to establish the stability of these signals which is critical for reproducibility.

Methods:

We examined 18 healthy adults age 23 – 61 who completed three visits across three years. For each visit participants completed both a resting state MEG and structural MRI scan. MEG data were source imaged, and the cortical power in canonical frequency bands (delta, theta, alpha, beta, low gamma, high gamma) was computed Intra-class correlation coefficients (ICC) were then calculated across the cortex for each frequency band.

Results:

Over three years, power in the alpha and beta bands displayed the highest reliability estimates, while gamma showed the lowest estimates of three-year reliability. Spatially, delta, alpha, and beta all showed the highest degrees of reliability in the parietal cortex. Interestingly, the peak signal for each of these frequency bands was located outside of the parietal cortex, suggesting that reliability estimates were not solely dependent on the signal-to-noise ratio.

Conclusion:

Oscillatory resting-state power in parietal delta, posterior beta, and alpha across most of the cortex are reliable across three years and future MEEG studies may focus on these measures for the development of specific markers.

Human amygdala functional network development: A cross-sectional study from 3 months to 5 years of age

Although the amygdala's role in shaping social behavior is especially important during early post-natal development, very little is known of amygdala functional development before childhood. To address this gap, this study uses resting-state fMRI to examine early amygdalar functional network development in a cross-sectional sample of 80 children from 3-months to 5-years of age. Whole brain functional connectivity with the amygdala, and its laterobasal and superficial sub-regions, were largely similar to those seen in older children and adults. Functional distinctions between sub-region networks were already established. These patterns suggest many amygdala functional circuits are intact from infancy, especially those that are part of motor, visual, auditory and subcortical networks. Developmental changes in connectivity were observed between the laterobasal nucleus and bilateral ventral temporal and motor cortex as well as between the superficial nuclei and medial thalamus, occipital cortex and a different region of motor cortex. These results show amygdala-subcortical and sensory-cortex connectivity begins refinement prior to childhood, though connectivity changes with associative and frontal cortical areas, seen after early childhood, were not evident in this age range. These findings represent early steps in understanding amygdala network dynamics across infancy through early childhood, an important period of emotional and cognitive development.

Increases in Intrinsic Thalamocortical Connectivity and Overall Cognition Following Cognitive Remediation in Chronic Schizophrenia

BACKGROUND

Thalamic projections to the prefrontal cortex (PFC) are critical for cognition, and disruptions in these circuits are thought to underlie the pathophysiology of schizophrenia. Cognitive remediation (REM) is a behavioral intervention that holds promise for improving cognition and functioning in schizophrenia, however the extent to which it affects thalamo-prefrontal connections has not been researched. This study sought to determine whether patients with schizophrenia who undergo a placebo-controlled trial of REM show increased functional connectivity between the thalamus and PFC, and whether these changes correspond to improvements in cognition.

METHODS

Twenty-six patients with chronic schizophrenia were randomized to either 48 hours (over 16 weeks) of a drill-and-practice working memory-focused REM or an active placebo condition. All participants underwent cognitive assessment (MATRICS Consensus Cognitive Battery), as well as both resting and task-based fMRI before and after their respective intervention. All clinicians, technicians, and raters were blind to participant condition.

RESULTS

We observed changes in resting-state connectivity in the PFC for the REM group but not the placebo group. Increased intrinsic connectivity between the thalamus and right middle frontal gyrus correlated with improvements in overall cognition. Additionally, lower baseline cognition correlated with greater increases in connectivity between the thalamus and PFC. Similar findings were observed when patients were scanned during a working memory task.

CONCLUSIONS

These results suggest that increases in thalamo-prefrontal circuitry correspond with training-related improvements of the cognitive deficits associated with schizophrenia.

Altered Dynamic of EEG Oscillations in Fibromyalgia Patients at Rest

OBJECTIVE

Previous fMRI findings have shown that chronic pain patients display an altered activation and functional connectivity of the pain network. The aim of the present study was to analyze EEG dynamics in fibromyalgia patients (n = 20) and pain-free controls (n = 18) at rest.

METHODS

Spectral power density, source current density, and intra- and inter-hemispheric coherence were analyzed from 64 EEG channels during 5-minutes eyes-closed rest.

RESULTS

Results indicated that fibromyalgia patients displayed reduced power density of the delta EEG band (2-4 Hz) over right insula, right superior and middle temporal gyri as compared with pain-free controls. Fibromyalgia patients also exhibited greater power density than pain-free controls in two segments of the beta band (16-23 Hz and 23-30 Hz) over right middle frontal lobe and midcingulate gyrus. Pain duration in fibromyalgia patients was negatively correlated with delta power from right insula. Greater centro-parietal intra-hemispheric coherence was observed at the left hemisphere on theta (4-8 Hz), and beta-3 (23-30 Hz) frequency bands in fibromyalgia patients than in pain-free controls. Individual differences in depression, anxiety or negative affect did not account for these findings.

CONCLUSIONS

Fibromyalgia leads to an altered dynamic of the brain network involved in the processing of pain even at rest. Furthermore ,: our results provide further support for the feasibility of resting-state EEG analyses as a clinical biomarker for the characterization of chronic pain states.

Diminished functional connectivity on the road to child sexual abuse in pedophilia

BACKGROUND

Pedophilia is a disorder recognized for its impairment to the individual and for the harm it may cause to others. However, the neurobiology of pedophilia and a possible propensity to sexually abuse children are not well understood. In this study, we thus aimed at providing new insights in how functional integration of brain regions may relate to pedophilia or child sexual abuse (CSA).

METHOD

By using functional magnetic resonance imaging (fMRI) technique, we compared functional connectivity at rest (RSFC) between pedophiles who engaged (P+CSA; N = 12) or did not engage (P-CSA; N = 14) in CSA and healthy controls (HCs; N = 14) within two networks: (i) the default mode network and (ii) the limbic network that has been linked to pedophilia before.

RESULTS

Pedophiles who engaged in CSA show diminished RSFC in both networks compared with HC and P-CSA. Most importantly, they showed diminished RSFC between the left amygdala and orbitofrontal as well as anterior prefrontal regions. Though significant age differences between groups could not be avoided, correlation control analysis did not provide evidence for the assumption that the RSFC effects were related to age differences.

CONCLUSION

We found significantly diminished RSFC in brain networks critically involved in widespread motivational and socio-emotional processes. These results extend existing models of the functional neuroanatomy of pedophilia and CSA as altered RSFC between these regions were related to CSA rather than pedophilia and thus may account for an increased propensity to engage in CSA in people suffering from pedophilia.

Using functional Magnetic Resonance Imaging to differentiate between healthy aging subjects, Mild Cognitive Impairment, and Alzheimer's patients

BACKGROUND

Alzheimer's disease is the most common form of dementia which is still difficult to be differentiated from other types of brain disorders. Moreover, Mild Cognitive Impairment refers to the presence of cognitive impairments that is not severe enough to meet the criteria of Alzheimer's, and its diagnosis in early stages is so critical. There is currently no distinct method available for diagnosing Alzheimer's or Mild Cognitive Impairment, and their diagnosis needs a combination of different methods and assessments.

METHODS

The aim of this study was to evaluate the effectiveness of functional Magnetic Resonance Imaging (fMRI) in differentiating between Alzheimer's, Mild Cognitive Impairment (MCI) and healthy aging. To prove fMRI's ability, resting-state brain activation patterns between these three groups of subjects were compared using Independent Component Analysis (ICA) algorithm. Forty age- and sex-matched subjects, 15 elderly, 11 MCI and 14 Alzheimer's subjects were examined.

RESULTS

The results showed that during a certain resting-state session, healthy aging brain benefits from larger area and greater intensity of activation (compared with MCI and Alzheimer's group) in Posterior Cingulate Cortex (PCC) region of the brain, as part of Default Mode Network.

CONCLUSIONS

This difference in activation pattern can be used as a diagnostic criterion in using fMRI for differentiating between Alzheimer's Disease (AD), MCI and healthy aging.