Identifying neuroanatomical signatures in insomnia and migraine comorbidity

SLEEP ◽  
2020 ◽  
Author(s):  
Kun-Hsien Chou ◽  
Pei-Lin Lee ◽  
Chih-Sung Liang ◽  
Jiunn-Tay Lee ◽  
Hung-Wen Kao ◽  
...  
Keyword(s):  
Large Scale ◽  
Gray Matter Volume ◽  
Brain Structures ◽  
Brain Network ◽  
Structural Covariance ◽  
Matter Volume ◽  
The Right ◽  
Global Brain ◽  
The Brain

Abstract Study Objectives While insomnia and migraine are often comorbid, the shared and distinct neuroanatomical substrates underlying these disorders and the brain structures associated with the comorbidity are unknown. We aimed to identify patterns of neuroanatomical substrate alterations associated with migraine and insomnia comorbidity. Methods High-resolution T1-weighted images were acquired from subjects with insomnia, migraine, and comorbid migraine and insomnia, respectively, and healthy controls (HC). Direct group comparisons with HC followed by conjunction analyses identified shared regional gray matter volume (GMV) alterations between the disorders. To further examine large-scale anatomical network changes, a seed-based structural covariance network (SCN) analysis was applied. Conjunction analyses also identified common SCN alterations in two disease groups, and we further evaluated these shared regional and global neuroanatomical signatures in the comorbid group. Results Compared with controls, patients with migraine and insomnia showed GMV changes in the cerebellum and the lingual, precentral, and postcentral gyri (PCG). The bilateral PCG were common GMV alteration sites in both groups, with decreased structural covariance integrity observed in the cerebellum. In patients with comorbid migraine and insomnia, shared regional GMV and global SCN changes were consistently observed. The GMV of the right PCG also correlated with sleep quality in these patients. Conclusion These findings highlight the specific role of the PCG in the shared pathophysiology of insomnia and migraine from a regional and global brain network perspective. These multilevel neuroanatomical changes could be used as potential image markers to decipher the comorbidity of the two disorders.

scholarly journals Effects of Meditation on Structural Changes of the Brain in Patients With Mild Cognitive Impairment or Alzheimer’s Disease Dementia

2021 ◽  
Vol 15 ◽  
Author(s):  
Madhukar Dwivedi ◽  
Neha Dubey ◽  
Aditya Jain Pansari ◽  
Raju Surampudi Bapi ◽  
Meghoranjani Das ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Cortical Thickness ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Brain Areas ◽  
Hippocampal Subfields ◽  
Matter Volume ◽  
The Right ◽  
The Brain

Previous cross-sectional studies reported positive effects of meditation on the brain areas related to attention and executive function in the healthy elderly population. Effects of long-term regular meditation in persons with mild cognitive impairment (MCI) and Alzheimer’s disease dementia (AD) have rarely been studied. In this study, we explored changes in cortical thickness and gray matter volume in meditation-naïve persons with MCI or mild AD after long-term meditation intervention. MCI or mild AD patients underwent detailed clinical and neuropsychological assessment and were assigned into meditation or non-meditation groups. High resolution T1-weighted magnetic resonance images (MRI) were acquired at baseline and after 6 months. Longitudinal symmetrized percentage changes (SPC) in cortical thickness and gray matter volume were estimated. Left caudal middle frontal, left rostral middle frontal, left superior parietal, right lateral orbitofrontal, and right superior frontal cortices showed changes in both cortical thickness and gray matter volume; the left paracentral cortex showed changes in cortical thickness; the left lateral occipital, left superior frontal, left banks of the superior temporal sulcus (bankssts), and left medial orbitofrontal cortices showed changes in gray matter volume. All these areas exhibited significantly higher SPC values in meditators as compared to non-meditators. Conversely, the left lateral occipital, and right posterior cingulate cortices showed significantly lower SPC values for cortical thickness in the meditators. In hippocampal subfields analysis, we observed significantly higher SPC in gray matter volume of the left CA1, molecular layer HP, and CA3 with a trend for increased gray matter volume in most other areas. No significant changes were found for the hippocampal subfields in the right hemisphere. Analysis of the subcortical structures revealed significantly increased volume in the right thalamus in the meditation group. The results of the study point out that long-term meditation practice in persons with MCI or mild AD leads to salutary changes in cortical thickness and gray matter volumes. Most of these changes were observed in the brain areas related to executive control and memory that are prominently at risk in neurodegenerative diseases.

Gray Matter Volume in Elderly adults With ADHD: Associations of Symptoms and Comorbidities With Brain Structures

2019 ◽  
pp. 108705471985568
Author(s):  
Margarete Klein ◽  
Fábio Luis Souza-Duran ◽  
Anny Karinna Pires Mendes Menezes ◽  
Tania Maria Alves ◽  
Geraldo Busatto ◽  
...  
Keyword(s):  
Gray Matter ◽  
Gray Matter Volume ◽  
Region Of Interest ◽  
Brain Structures ◽  
Anterior Cingulate ◽  
Affective Processing ◽  
Old Patients ◽  
Matter Volume ◽  
Magnetic Resonance Imaging Mri ◽  
The Right

Objective: To investigate total and selected region-of-interest-based gray matter volume (GMV) in older adults with ADHD. Method: Twenty-five elderly (≥65 years old) patients with ADHD and 34 healthy controls underwent 1.5-T magnetic resonance imaging (MRI). We used voxel-based morphometry to compare GMV between groups and performed a correlation analysis with ADHD symptoms and comorbidities. Results: Findings revealed a smaller total GMV in males with ADHD and a smaller GMV in the right medial frontal orbital area extending toward the medial frontal superior, the frontal superior, and the subgenual anterior cingulate cortex (ACC) besides correlations between inattentiveness and ACC (bilaterally) and left cerebellum, hyperactivity/impulsivity and the left frontal inferior orbital, depression and caudate (bilaterally), and the right inferior parietal lobule. Conclusion: Neural correlates in regions related to attention, executive control, and affective processing suggest that impairments in frontostriatal and frontoparietal-cerebellar areas observed in adults with ADHD persist into old age.

scholarly journals Optimism and the brain: trait optimism mediates the protective role of the orbitofrontal cortex gray matter volume against anxiety

2015 ◽  
Vol 11 (2) ◽  
pp. 263-271 ◽  
Author(s):  
Sanda Dolcos ◽  
Yifan Hu ◽  
Alexandru D. Iordan ◽  
Matthew Moore ◽  
Florin Dolcos
Keyword(s):  
Gray Matter ◽  
Orbitofrontal Cortex ◽  
Gray Matter Volume ◽  
Protective Role ◽  
Matter Volume ◽  
The Brain

scholarly journals Functional brain network topology across the menstrual cycle is sex hormone dependent and correlates with the individual well-being

2020 ◽  
Author(s):  
Marianna Liparoti ◽  
Emahnuel Troisi Lopez ◽  
Laura Sarno ◽  
Rosaria Rucco ◽  
Roberta Minino ◽  
...  
Keyword(s):  
Menstrual Cycle ◽  
Large Scale ◽  
Affective State ◽  
Well Being ◽  
Brain Network ◽  
Subjective Well Being ◽  
Functional Brain Network ◽  
The Individual ◽  
The Right ◽  
The Brain

AbstractThe menstrual cycle is known to influence the behaviour. The neuronal bases of this phenomenon are poorly understood. We hypothesized that hormones, might affect the large-scale organization of the brain functional networks and that, in turn, such changes might have behavioural correlates in terms of the affective state. To test our hypothesis, we took advantage of magnetoencephalography to investigate brain topology in early follicular, ovulatory and luteal phases, in twenty-four naturally-cycling women without signs of anxiety and/or depression. We show that in the alpha band the betweenness centrality (BC) of the right posterior cingulate gyrus (PCG) during the ovulatory phase is increased and the rise is predicted by the levels of estradiol. We also demonstrate that the increase in the BC is related to improved subjective well-being that, in turn, is correlated to the estradiol levels. The increased topological centrality of the PCG during the ovulatory phase could have implications in reproductive psychology.

A new method to predict anomaly in brain network based on graph deep learning

2020 ◽  
Vol 31 (6) ◽  
pp. 681-689
Author(s):  
Jalal Mirakhorli ◽  
Hamidreza Amindavar ◽  
Mojgan Mirakhorli
Keyword(s):  
Deep Learning ◽  
Large Scale ◽  
Brain Plasticity ◽  
Brain Network ◽  
High Order ◽  
Brain Diseases ◽  
Simultaneous Occurrence ◽  
Generative Adversarial Network ◽  
The Brain ◽  
Brain Connections

AbstractFunctional magnetic resonance imaging a neuroimaging technique which is used in brain disorders and dysfunction studies, has been improved in recent years by mapping the topology of the brain connections, named connectopic mapping. Based on the fact that healthy and unhealthy brain regions and functions differ slightly, studying the complex topology of the functional and structural networks in the human brain is too complicated considering the growth of evaluation measures. One of the applications of irregular graph deep learning is to analyze the human cognitive functions related to the gene expression and related distributed spatial patterns. Since a variety of brain solutions can be dynamically held in the neuronal networks of the brain with different activity patterns and functional connectivity, both node-centric and graph-centric tasks are involved in this application. In this study, we used an individual generative model and high order graph analysis for the region of interest recognition areas of the brain with abnormal connection during performing certain tasks and resting-state or decompose irregular observations. Accordingly, a high order framework of Variational Graph Autoencoder with a Gaussian distributer was proposed in the paper to analyze the functional data in brain imaging studies in which Generative Adversarial Network is employed for optimizing the latent space in the process of learning strong non-rigid graphs among large scale data. Furthermore, the possible modes of correlations were distinguished in abnormal brain connections. Our goal was to find the degree of correlation between the affected regions and their simultaneous occurrence over time. We can take advantage of this to diagnose brain diseases or show the ability of the nervous system to modify brain topology at all angles and brain plasticity according to input stimuli. In this study, we particularly focused on Alzheimer’s disease.

scholarly journals Voxel-based correlation of 18F-THK5351 accumulation and gray matter volume in the brain of cognitively normal older adults

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Yoko Shigemoto ◽  
Daichi Sone ◽  
Miho Ota ◽  
Norihide Maikusa ◽  
Masayo Ogawa ◽  
...  
Keyword(s):  
Older Adults ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Cognitively Normal ◽  
Matter Volume ◽  
The Brain

scholarly journals Peptides Derived from Growth Factors to Treat Alzheimer’s Disease

2021 ◽  
Vol 22 (11) ◽  
pp. 6071
Author(s):  
Suzanne Gascon ◽  
Jessica Jann ◽  
Chloé Langlois-Blais ◽  
Mélanie Plourde ◽  
Christine Lavoie ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Growth Factors ◽  
Signaling Pathways ◽  
Brain Structures ◽  
Therapeutic Strategies ◽  
Native Proteins ◽  
Receptor Sites ◽  
The Brain

Alzheimer’s disease (AD) is a devastating neurodegenerative disease characterized by progressive neuron losses in memory-related brain structures. The classical features of AD are a dysregulation of the cholinergic system, the accumulation of amyloid plaques, and neurofibrillary tangles. Unfortunately, current treatments are unable to cure or even delay the progression of the disease. Therefore, new therapeutic strategies have emerged, such as the exogenous administration of neurotrophic factors (e.g., NGF and BDNF) that are deficient or dysregulated in AD. However, their low capacity to cross the blood–brain barrier and their exorbitant cost currently limit their use. To overcome these limitations, short peptides mimicking the binding receptor sites of these growth factors have been developed. Such peptides can target selective signaling pathways involved in neuron survival, differentiation, and/or maintenance. This review focuses on growth factors and their derived peptides as potential treatment for AD. It describes (1) the physiological functions of growth factors in the brain, their neuronal signaling pathways, and alteration in AD; (2) the strategies to develop peptides derived from growth factor and their capacity to mimic the role of native proteins; and (3) new advancements and potential in using these molecules as therapeutic treatments for AD, as well as their limitations.

scholarly journals Consciousness, decision making, and volition: freedom beyond chance and necessity

2021 ◽  
Author(s):  
Hans Liljenström
Keyword(s):  
Decision Making ◽  
Free Will ◽  
Brain Activity ◽  
Brain Structures ◽  
Complex Process ◽  
Neural Information ◽  
Neural Information Processing ◽  
Stochastic Population Model ◽  
The Brain

AbstractWhat is the role of consciousness in volition and decision-making? Are our actions fully determined by brain activity preceding our decisions to act, or can consciousness instead affect the brain activity leading to action? This has been much debated in philosophy, but also in science since the famous experiments by Libet in the 1980s, where the current most common interpretation is that conscious free will is an illusion. It seems that the brain knows, up to several seconds in advance what “you” decide to do. These studies have, however, been criticized, and alternative interpretations of the experiments can be given, some of which are discussed in this paper. In an attempt to elucidate the processes involved in decision-making (DM), as an essential part of volition, we have developed a computational model of relevant brain structures and their neurodynamics. While DM is a complex process, we have particularly focused on the amygdala and orbitofrontal cortex (OFC) for its emotional, and the lateral prefrontal cortex (LPFC) for its cognitive aspects. In this paper, we present a stochastic population model representing the neural information processing of DM. Simulation results seem to confirm the notion that if decisions have to be made fast, emotional processes and aspects dominate, while rational processes are more time consuming and may result in a delayed decision. Finally, some limitations of current science and computational modeling will be discussed, hinting at a future development of science, where consciousness and free will may add to chance and necessity as explanation for what happens in the world.

The gray matter volume of the right insula mediates the relationship between symptoms of depression/anxiety and sleep quality among college students

2019 ◽  
pp. 135910531986997 ◽  
Author(s):  
Huazhan Yin ◽  
Li Zhang ◽  
Dan Li ◽  
Lu Xiao ◽  
Mei Cheng
Keyword(s):  
College Students ◽  
Sleep Quality ◽  
Gray Matter ◽  
Emotional Processing ◽  
Gray Matter Volume ◽  
Critical Role ◽  
Symptoms Of Depression ◽  
Matter Volume ◽  
The Right ◽  
The Relationship

This study investigated the neuroanatomical basis of the association between depression/anxiety and sleep quality among 370 college students. The results showed that there was a significant correlation between sleep quality and depression/anxiety. Moreover, mediation results showed that the gray matter volume of the right insula mediated the relationship between depression/anxiety and sleep quality, which suggested that depression/anxiety may affect sleep quality through the right insula volume. These findings confirmed a strong link between sleep quality and depression/anxiety, while highlighting the volumetric variation in the right insula associated with emotional processing, which may play a critical role in improving sleep quality.

Sleep Duration, Sleep Apnea, and Gray Matter Volume

2021 ◽  
pp. 089198872098891
Author(s):  
Regina Eun Young Kim ◽  
Robert Douglas Abbott ◽  
Soriul Kim ◽  
Robert Joseph Thomas ◽  
Chang-Ho Yun ◽  
...  
Keyword(s):  
Sleep Apnea ◽  
Sleep Duration ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Brain Structures ◽  
Brain Regions ◽  
Population Based ◽  
Older Individuals ◽  
Bootstrap Sampling ◽  
Matter Volume

This study aimed to evaluate the effect of sleep duration on brain structures in the presence versus absence of sleep apnea in middle-aged and older individuals. The study investigated a population-based sample of 2,560 individuals, aged 49-80 years. The presence of sleep apnea and self-reported sleep duration were examined in relation to gray matter volume (GMV) in total and lobar brain regions. We identified ranges of sleep duration associated with maximal GMV using quadratic regression and bootstrap sampling. A significant quadratic association between sleep duration and GMV was observed in total and lobar brain regions of men with sleep apnea. In the fully adjusted model, optimal sleep durations associated with peak GMV between brain regions ranged from 6.7 to 7.0 hours. Shorter and longer sleep durations were associated with lower GMV in total and 4 sub-regions of the brain in men with sleep apnea.

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