Brain rhythms of pain

Pain is an integrative phenomenon that results from dynamic interactions between sensory and contextual (i.e., cognitive, emotional, and motivational) processes. In the brain the experience of pain is associated with neuronal oscillations and synchrony at different frequencies. However, an overarching framework for the significance of oscillations for pain remains lacking. Recent concepts relate oscillations at different frequencies to the routing of information flow in the brain and the signaling of predictions and prediction errors. The application of these concepts to pain promises insights into how flexible routing of information flow coordinates diverse processes that merge into the experience of pain. Such insights might have implications for the understanding and treatment of chronic pain

Measuring cortical connectivity in Alzheimer's disease as a brain neural network pathology: Toward clinical applications

Objectives: The objective was to review the literature on diffusion tensor imaging as well as resting-state functional magnetic resonance imaging and electroencephalography (EEG) to unveil neuroanatomical and neurophysiological substrates of Alzheimer’s disease (AD) as a brain neural network pathology affecting structural and functional cortical connectivity underlying human cognition. Methods: We reviewed papers registered in PubMed and other scientific repositories on the use of these techniques in amnesic mild cognitive impairment (MCI) and clinically mild AD dementia patients compared to cognitively intact elderly individuals (Controls). Results: Hundreds of peer-reviewed (cross-sectional and longitudinal) papers have shown in patients with MCI and mild AD compared to Controls (1) impairment of callosal (splenium), thalamic, and anterior–posterior white matter bundles; (2) reduced correlation of resting state blood oxygen level-dependent activity across several intrinsic brain circuits including default mode and attention-related networks; and (3) abnormal power and functional coupling of resting state cortical EEG rhythms. Clinical applications of these measures are still limited. Conclusions: Structural and functional (in vivo) cortical connectivity measures represent a reliable marker of cerebral reserve capacity and should be used to predict and monitor the evolution of AD and its relative impact on cognitive domains in pre-clinical, prodromal, and dementia stages of AD. (JINS, 2016, 22, 138–163

Trauma Innovations: MDMA as a Treatment Intervention for PTSD

Aims: To examine the evidence displayed across 3 distinct communities (popular, scientific, & clinical) in conjunction with the use of MDMA-AP as an intervention for PTSD. Method: A mixed method synthesis of qualitative and quantitative research. Data Sources: Four databases were searched [1980-Present] for MDMA & PTSD and/or Mithoefer, et al. 2010 specific scientific literature providing forty-two randomly selected articles; YouTube was searched specifically targeting the same criteria to provide forty-two randomly selected videos; 201 LICSW’s from Minnesota were also surveyed. Results: From the three datasets, three common themes emerged: (1) attitudes specifically geared toward MDMA-AP; (2) effusive or willful language; and (3) gaps in the research. Conclusions: Scientific literature is neutral to somewhat supportive of more study of MDMA-AP; primary source videos consider the topic highly newsworthy and are generally supportive of more study; LICSWs are supportive of the idea of further study of MDMA-AP

Trauma Innovations: MDMA as a Treatment Intervention for PTSD

Aims: To examine the evidence displayed across 3 distinct communities (popular, scientific, & clinical) in conjunction with the use of MDMA-AP as an intervention for PTSD. Method: A mixed method synthesis of qualitative and quantitative research. Data Sources: Four databases were searched [1980-Present] for MDMA & PTSD and/or Mithoefer, et al. 2010 specific scientific literature providing forty-two randomly selected articles; YouTube was searched specifically targeting the same criteria to provide forty-two randomly selected videos; 201 LICSW\u27s from Minnesota were also surveyed. Results: From the three datasets, three common themes emerged: (1) attitudes specifically geared toward MDMA-AP; (2) effusive or willful language; and (3) gaps in the research. Conclusions: Scientific literature is neutral to somewhat supportive of more study of MDMA-AP; primary source videos consider the topic highly newsworthy and are generally supportive of more study; LICSWs are supportive of the idea of further study of MDMA-AP

Head growth and intelligence from birth to adulthood in very preterm and term born individuals

Objectives: The aim of this study was to investigate the effects of infant and toddler head growth on intelligence scores from early childhood to adulthood in very preterm (<32 weeks gestational age; VP) and/or very low birth weight (<1500 g; VLBW) and term born individuals. Methods: 203 VP/VLBW and 198 term comparisons were studied from birth to adulthood as part of the prospective geographically defined Bavarian Longitudinal Study (BLS). Head circumference was assessed at birth; 5, 20 months; and 4 years of age. Intelligence was assessed with standardized tests in childhood (6 and 8 years: K-ABC) and at 26 years (Wechsler Adult Intelligence Scale, WAIS). Structural equation modeling (SEM) was used to model the effect of head growth on IQ. Results: On average, VP/VLBW had lower head circumference at birth (27.61 cm vs. 35.11 cm, mean difference 7.49, 95% confidence interval [7.09–7.90]) and lower adult intelligence scores (88.98 vs. 102.54, mean difference 13.56 [10.59–16.53]) than term born comparison individuals. Head circumference at birth (e.g., total effect β=.48; p<.001 for adult IQ) and head growth in childhood predicted intelligence development from age 6 to 26 years in both VP/VLBW and term born individuals (70% of variance in adult IQ explained by full model). Effects of gestation and birth weight on intelligence were fully mediated by head circumference and growth. Conclusions: This longitudinal investigation from birth to adulthood indicates head growth as a proxy of brain development and intelligence. Repeated early head circumference assessment adds valuable information when screening for long-term neurocognitive risk. (JINS, 2019, 25, 48#x2013;56

An analysis of MRI derived cortical complexity in premature-born adults : regional patterns, risk factors, and potential significance

Premature birth bears an increased risk for aberrant brain development concerning its structure and function. Cortical complexity (CC) expresses the fractal dimension of the brain surface and changes during neurodevelopment. We hypothesized that CC is altered after premature birth and associated with long-term cognitive development. One-hundred-and-one very premature-born adults (gestational age <32 weeks and/or birth weight <1500 ​g) and 111 term-born adults were assessed by structural MRI and cognitive testing at 26 years of age. CC was measured based on MRI by vertex-wise estimation of fractal dimension. Cognitive performance was measured based on Griffiths-Mental-Development-Scale (at 20 months) and Wechsler-Adult-Intelligence-Scales (at 26 years). In premature-born adults, CC was decreased bilaterally in large lateral temporal and medial parietal clusters. Decreased CC was associated with lower gestational age and birth weight. Furthermore, decreased CC in the medial parietal cortices was linked with reduced full-scale IQ of premature-born adults and mediated the association between cognitive development at 20 months and IQ in adulthood. Results demonstrate that CC is reduced in very premature-born adults in temporoparietal cortices, mediating the impact of prematurity on impaired cognitive development. These data indicate functionally relevant long-term alterations in the brain’s basic geometry of cortical organization in prematurity

Perspectives on How Human simultaneous Multi-Modal imaging Adds Directionality to spread Models of Alzheimer's Disease

Previous animal research suggests that the spread of pathological agents in Alzheimer's disease (AD) follows the direction of signaling pathways. Specifically, tau pathology has been suggested to propagate in an infection-like mode along axons, from transentorhinal cortices to medial temporal lobe cortices and consequently to other cortical regions, while amyloid-beta (A beta) pathology seems to spread in an activity-dependent manner among and from isocortical regions into limbic and then subcortical regions. These directed connectivity-based spread models, however, have not been tested directly in AD patients due to the lack of an in vivo method to identify directed connectivity in humans. Recently, a new method-metabolic connectivity mapping (MCM)-has been developed and validated in healthy participants that uses simultaneous FDG-PET and resting-state fMRI data acquisition to identify directed intrinsic effective connectivity (EC). To this end, postsynaptic energy consumption (FDG-PET) is used to identify regions with afferent input from other functionally connected brain regions (resting-state fMRI). Here, we discuss how this multi-modal imaging approach allows quantitative, whole-brain mapping of signaling direction in AD patients, thereby pointing out some of the advantages it offers compared to other EC methods (i.e., Granger causality, dynamic causal modeling, Bayesian networks). Most importantly, MCM provides the basis on which models of pathology spread, derived from animal studies, can be tested in AD patients. In particular, future work should investigate whether tau and A beta in humans propagate along the trajectories of directed connectivity in order to advance our understanding of the neuropathological mechanisms causing disease progression

Grading of Frequency Spectral Centroid Across Resting-State Networks

Ongoing, slowly fluctuating brain activity is organized in resting-state networks (RSNs) of spatially coherent fluctuations. Beyond spatial coherence, RSN activity is governed in a frequency-specific manner. The more detailed architecture of frequency spectra across RSNs is, however, poorly understood. Here we propose a novel measure–the Spectral Centroid (SC)–which represents the center of gravity of the full power spectrum of RSN signal fluctuations. We examine whether spectral underpinnings of network fluctuations are distinct across RSNs. We hypothesize that spectral content differs across networks in a consistent way, thus, the aggregate representation–SC–systematically differs across RSNs. We therefore test for a significant grading (i.e., ordering) of SC across RSNs in healthy subjects. Moreover, we hypothesize that such grading is biologically significant by demonstrating its RSN-specific change through brain disease, namely major depressive disorder. Our results yield a highly organized grading of SC across RSNs in 820 healthy subjects. This ordering was largely replicated in an independent dataset of 25 healthy subjects, pointing toward the validity and consistency of found SC grading across RSNs. Furthermore, we demonstrated the biological relevance of SC grading, as the SC of the salience network–a RSN well known to be implicated in depression–was specifically increased in patients compared to healthy controls. In summary, results provide evidence for a distinct grading of spectra across RSNs, which is sensitive to major depression

Frequency-Dependent Spatial Distribution of Functional Hubs in the Human Brain and Alterations in Major Depressive Disorder

Alterations in large-scale brain intrinsic functional connectivity (FC), i.e., coherence between fluctuations of ongoing activity, have been implicated in major depressive disorder (MDD). Yet, little is known about the frequency-dependent alterations of FC in MDD. We calculated frequency specific degree centrality (DC) – a measure of overall FC of a brain region – within 10 distinct frequency sub-bands accessible from the full range of resting-state fMRI BOLD fluctuations (i.e., 0.01–0.25 Hz) in 24 healthy controls and 24 MDD patients. In healthy controls, results reveal a frequency-specific spatial distribution of highly connected brain regions – i.e., hubs – which play a fundamental role in information integration in the brain. MDD patients exhibited significant deviations from the healthy DC patterns, with decreased overall connectedness of widespread regions, in a frequency-specific manner. Decreased DC in MDD patients was observed predominantly in the occipital cortex at low frequencies (0.01–0.1 Hz), in the middle cingulate cortex, sensorimotor cortex, lateral parietal cortex, and the precuneus at middle frequencies (0.1–0.175 Hz), and in the anterior cingulate cortex at high frequencies (0.175–0.25 Hz). Additionally, decreased DC of distinct parts of the insula was observed across low, middle, and high frequency bands. Frequency-specific alterations in the DC of the temporal, insular, and lateral parietal cortices correlated with symptom severity. Importantly, our results indicate that frequency-resolved analysis within the full range of frequencies accessible from the BOLD signal – also including higher frequencies (&gt;0.1 Hz) – reveals unique information about brain organization and its changes, which can otherwise be overlooked

Sequelae of premature birth in young adults

Background and Purpose Qualitative studies about the abnormalities appreciated on routine magnetic resonance imaging (MRI) sequences in prematurely born adults are lacking. This article aimed at filling this knowledge gap by (1) qualitatively describing routine imaging findings in prematurely born adults, (2) evaluating measures for routine image interpretation and (3) investigating the impact of perinatal variables related to premature birth. Methods In this study two board-certified radiologists assessed T1-weighted and FLAIR-weighted images of 100 prematurely born adults born very preterm (VP <32 weeks) and/or at very low birth weight (VLBW <1500 g) and 106 controls born at full term (FT) (mean age 26.8 ± 0.7 years). The number of white matter lesions (WML) was counted according to localization. Lateral ventricle volume (LVV) was evaluated subjectively and by measurements of Evans’ index (EI) and frontal-occipital-horn ratio (FOHR). Freesurfer-based volumetry served as reference standard. Miscellaneous incidental findings were noted as free text. Results The LVV was increased in 24.7% of VP/VLBW individuals and significantly larger than in FT controls. This was best identified by measurement of FOHR (AUC = 0.928). Ventricular enlargement was predicted by low gestational age (odds ratio: 0.71, 95% CI 0.51–0.98) and presence of neonatal intracranial hemorrhage (odds ratio: 0.26, 95% CI 0.07–0.92). The numbers of deep and periventricular WML were increased while subcortical WMLs were not. Conclusion Enlargement of the LVV and deep and periventricular WMLs are typical sequelae of premature birth that can be appreciated on routine brain MRI. To increase sensitivity of abnormal LVV detection, measurement of FOHR seems feasible in clinical practice